KR20240087718A - Motion vector difference sign prediction for video coding - Google Patents

Abstract

The video decoder constructs motion vector candidates using the possible sign values, the respective sizes of the motion vector difference components, and a motion vector predictor for the block of video data, where the possible sign values are a positive sign value and a negative sign value. Construct the motion vector candidates, including the values; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

Description

Motion vector difference sign prediction for video coding

This application claims the benefit of U.S. Provisional Patent Application No. 63/249,421, filed September 28, 2021, and U.S. Provisional Patent Application No. 17/929,122, filed September 1, 2022, the entire contents of which are incorporated herein by reference. Incorporated herein by reference. U.S. Patent Application No. 17/929,122 claims the benefit of U.S. Provisional Patent Application No. 63/249,421, filed September 28, 2021.

This disclosure relates to video encoding and video decoding.

Digital video capabilities include digital televisions, digital direct broadcast systems, wireless broadcast systems, personal digital assistants (PDAs), laptop or desktop computers, tablet computers, e-book readers, digital cameras, and digital cameras. A wide range of devices, including recording devices, digital media players, video gaming devices, video game consoles, cellular or satellite wireless phones, so-called “smart phones,” video teleconferencing devices, video streaming devices, etc. can be integrated. Digital video devices support MPEG-2, MPEG-4, ITU-T H.263, ITU-T H.264/MPEG-4, Part 10, Advanced Video Coding (AVC), and ITU-T H.265/High Efficiency Video. Video coding techniques such as those described in the standards defined by ITU-T H.266/Versatile Video Coding (VVC), and extensions of those standards, as well as the Alliance for Open Media Coding (HEVC), Implements proprietary video codecs/formats such as AV1 (AOMedia Video 1) developed by Media. Video devices may transmit, receive, encode, decode, and/or store digital video information more efficiently by implementing such video coding techniques.

Video coding techniques include spatial (intra picture) prediction and/or temporal (inter picture) prediction to reduce or remove redundancy inherent in video sequences. For block-based video coding, a video slice (e.g., a video picture or a portion of a video picture) may be partitioned into video blocks, which are divided into coding tree units (CTUs), coding units (CUs) s) and/or coding nodes. Video blocks in an intra-coded (I) slice of a picture are encoded using spatial prediction with respect to reference samples in neighboring blocks of the same picture. Video blocks in an inter-coded (P or B) slice of a picture may use spatial prediction relative to reference samples in neighboring blocks of the same picture or temporal prediction relative to reference samples in other reference pictures. . Pictures may be referred to as frames, and reference pictures may be referred to as reference frames.

In general, this disclosure describes techniques for inter prediction and inter-related information coding. More specifically, devices and techniques for predicting the sign of MVD (motion vector difference) are described. MVD is the difference between the motion vector determined for a specific coding mode and the motion vector predicted using a specific motion vector prediction method. MVD can be expressed as the difference between the predicted and determined motion vectors in both the X and Y directions (e.g., called motion vector difference coordinates).

The MVD may include both the absolute value of the difference (e.g., magnitude) as well as the polarity or sign of the difference (e.g., positive or negative). Signaling information representing the sign of MVD coordinates may consume a large amount of bandwidth in overhead signaling. This disclosure describes techniques for predicting the sign of MVD coordinates for one or more coding modes using MVD. For example, the techniques of the present disclosure include merge mode with MVD (MMVD) coding mode, affine MMVD, geometric partitioning mode (GPM) with MMVD, multiple hypothesis prediction (MHP) mode, or MVD. Alternatively, it can be used for MVDs generated in other coding modes where it may be advantageous to predict the signs of different motion vectors. The techniques of this disclosure may improve coding efficiency of such coding modes.

In one example, this disclosure describes a method of decoding video data, which method uses the possible sign values, the respective magnitudes of the motion vector difference components, and a motion vector predictor for a block of video data to determine the motion vector. Constructing candidates, wherein possible sign values include positive sign values and negative sign values; Sorting the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determining each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decoding the block of video data using the respective magnitudes of the motion vector difference coordinates and the respective motion vector difference sign for each motion vector difference component.

In another example, the present disclosure describes an apparatus configured to decode video data, the apparatus comprising a memory configured to store a block of video data, and one or more processors in communication with the memory, wherein the one or more processors are capable of decoding video data. constructing motion vector candidates using the values, respective magnitudes of the motion vector difference components, and a motion vector predictor for a block of video data, wherein possible sign values include positive sign values and negative sign values. construct the motion vector candidates; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

In another example, this disclosure describes an apparatus configured to decode video data, wherein the apparatus determines the possible sign values, the respective magnitudes of the motion vector difference components, and the motion vector predictor for a block of video data. means for constructing vector candidates, wherein possible sign values include positive sign values and negative sign values; means for sorting the motion vector candidates based on a cost for each of the motion vector candidates to produce an ordered list; means for determining each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the ordered list; and means for decoding the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

In another example, the disclosure describes a non-transitory computer-readable storage medium storing instructions that, when executed, cause one or more processors configured to decode video data, describing a method of decoding video data; This method allows constructing motion vector candidates using the possible sign values, the respective magnitudes of the motion vector difference components, and a motion vector predictor for a block of video data, where the possible sign values are positive sign values and negative sign values. construct the motion vector candidates, including a sign value; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using each magnitude of the motion vector difference coordinates and each motion vector difference sign for each motion vector difference component.

Details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects and advantages will become apparent from the description and drawings, and the claims.

1 is a block diagram illustrating an example video encoding and decoding system that may perform the techniques of this disclosure.
2 is a conceptual diagram illustrating an example simplified affine motion model.
3 is a conceptual diagram illustrating example merge mode with motion vector difference (MMVD) search points.
Figure 4 is a conceptual diagram showing an example of geometric partitioning mode (GPM) partitions grouped at the same angle.
Figure 5 shows example frequency responses of two interpolation filters.
6 is a conceptual diagram illustrating an example of template matching performed on a search area around an initial motion vector.
7 is a conceptual diagram illustrating an example of motion vector sign prediction for translational inter blocks using template matching.
8 is a block diagram illustrating an example video encoder that may perform the techniques of this disclosure.
9 is a block diagram illustrating an example video decoder that may perform the techniques of this disclosure.
10 is a flowchart illustrating an example method for encoding a current block in accordance with the techniques of this disclosure.
11 is a flow chart illustrating an example method for decoding a current block in accordance with the techniques of this disclosure.
12 is a flow chart illustrating another example method for decoding a current block in accordance with the techniques of this disclosure.

Various coding modes, such as inter prediction, use motion vectors to determine prediction blocks. In some examples, instead of signaling the coordinates of a motion vector, the video encoder may signal a motion vector difference (MVD). MVD is the difference between the motion vector determined for a specific coding mode and the motion vector predicted using a specific motion vector prediction method. MVD can be expressed as the difference between the predicted and determined motion vectors in both the X and Y directions (e.g., called motion vector difference coordinates).

The MVD may include both the absolute value of the difference (e.g., magnitude) as well as the polarity or sign of the difference (e.g., positive or negative). Signaling information representing the sign of MVD coordinates may consume a large amount of bandwidth in overhead signaling. This disclosure describes techniques for predicting the sign of MVD coordinates for one or more coding modes using MVD. For example, the techniques of the present disclosure include merge mode with MVD (MMVD) coding mode, affine MMVD, geometric partitioning mode (GPM) with MMVD, multiple hypothesis prediction (MHP) mode, or MVD. Alternatively, it can be used for MVDs generated in other coding modes where it may be advantageous to predict the signs of different motion vectors. The techniques of this disclosure may improve coding efficiency of such coding modes.

In one example of this disclosure, a video decoder constructs motion vector candidates using the possible sign values, the respective magnitudes of the motion vector difference components, and a motion vector predictor for a block of video data, wherein the possible sign values are Construct the motion vector candidates, comprising a sign value of and a negative sign value of; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

1 is a block diagram illustrating an example video encoding and decoding system 100 that may perform the techniques of this disclosure. Techniques of this disclosure generally relate to coding (encoding and/or decoding) video data. Generally, video data includes arbitrary data for processing video. Accordingly, video data may include raw, unencoded video, encoded video, decoded (e.g., reconstructed) video, and video metadata, such as signaling data.

As shown in FIG. 1 , system 100 includes a source device 102 that provides encoded video data to be decoded and displayed by a destination device 116 in this example. In particular, source device 102 provides video data to destination device 116 via computer-readable medium 110. Source device 102 and destination device 116 may include desktop computers, notebook (i.e., laptop) computers, mobile devices, tablet computers, set-top boxes, telephone handsets, such as smartphones, It may include any of a wide range of devices, including televisions, cameras, display devices, digital media players, video gaming consoles, video streaming devices, broadcast receiver devices, etc. In some cases, source device 102 and destination device 116 may be equipped for wireless communication, and thus may be referred to as wireless communication devices.

In the example of FIG. 1 , source device 102 includes video source 104, memory 106, video encoder 200, and output interface 108. Destination device 116 includes input interface 122, video decoder 300, memory 120, and display device 118. According to this disclosure, video encoder 200 of source device 102 and video decoder 300 of destination device 116 may be configured to apply techniques for motion vector difference sign prediction. Accordingly, source device 102 represents an example of a video encoding device, while destination device 116 represents an example of a video decoding device. In other examples, the source device and destination device may include other components or arrangements. For example, source device 102 may receive video data from an external video source, such as an external camera. Likewise, destination device 116 may interface with an external display device, rather than including an integrated display device.

System 100 as shown in FIG. 1 is only one example. In general, any digital video encoding and/or decoding device may perform techniques for motion vector difference sign prediction. Source device 102 and destination device 116 are just examples of such coding devices where source device 102 generates coded video data for transmission to destination device 116. This disclosure refers to a “coding” device as a device that performs coding (encoding and/or decoding) of data. Accordingly, video encoder 200 and video decoder 300 represent examples of coding devices, particularly a video encoder and video decoder, respectively. In some examples, source device 102 and destination device 116 may operate in a substantially symmetric manner such that each of source device 102 and destination device 116 includes video encoding and decoding components. As such, system 100 may support one-way or two-way video transmission between source device 102 and destination device 116, for example, for video streaming, video playback, video broadcasting, or video calling.

Generally, video source 104 represents a source of video data (i.e., raw, unencoded video data) and encodes the data for the pictures into a sequential series of pictures ( Also referred to as “frames”). Video source 104 of source device 102 may include a video capture device, such as a video camera, a video archive containing previously captured raw video, and/or a video feed interface for receiving video from a video content provider. It may be possible. As a further alternative, video source 104 may generate computer graphics-based data as source video, or as a combination of live video, archived video, and computer-generated video. In each case, video encoder 200 encodes captured, pre-captured, or computer-generated video data. Video encoder 200 may reorder the pictures from the received order (sometimes referred to as “display order”) into the coding order for coding. Video encoder 200 may generate a bitstream containing encoded video data. Source device 102 then transmits the encoded video onto computer-readable medium 110 via output interface 108 for reception and/or retrieval, e.g., by input interface 122 of destination device 116. Data can also be output.

Memory 106 of source device 102 and memory 120 of destination device 116 represent general-purpose memories. In some examples, memories 106, 120 may store raw video data, such as raw video from video source 104 and raw, decoded video data from video decoder 300. Additionally or alternatively, memories 106, 120 may store software instructions executable by, for example, video encoder 200 and video decoder 300, respectively. Although memory 106 and memory 120 are shown separately from video encoder 200 and video decoder 300 in this example, video encoder 200 and video decoder 300 may also serve functionally similar or equivalent purposes. It should be understood that it may include internal memories for Moreover, memories 106, 120 may store encoded video data, for example, output from video encoder 200 and input to video decoder 300. In some examples, portions of memories 106, 120 may be allocated as one or more video buffers, such as to store raw, decoded, and/or encoded video data.

Computer-readable medium 110 may represent any type of medium or device capable of transferring encoded video data from source device 102 to destination device 116. In one example, computer-readable medium 110 allows source device 102 to transmit encoded video data directly to destination device 116 in real time, e.g., via a radio frequency network or computer-based network. It represents a communication medium to enable this. Depending on a communication standard, such as a wireless communication protocol, output interface 108 may modulate a transmitted signal containing encoded video data and input interface 122 may demodulate a received transmitted signal. Communication media may include any wireless or wired communication medium, such as the radio frequency (RF) spectrum or one or more physical transmission lines. The communication medium may form part of a packet-based network, such as a local area network, a wide area network, or a global network such as the Internet. Communication media may include routers, switches, base stations, or any other equipment that may be useful to facilitate communication from source device 102 to destination device 116.

In some examples, source device 102 may output encoded data from output interface 108 to storage device 112. Similarly, destination device 116 may access encoded data from storage device 112 via input interface 122. Storage device 112 may be a variety of devices, such as hard drives, Blu-ray discs, DVDs, CD-ROMs, flash memory, volatile or non-volatile memory, or any other suitable digital storage medium for storing encoded video data. It may comprise any of distributed or locally accessed data storage media.

In some examples, source device 102 may output encoded video data to file server 114 or another intermediate storage device that may store encoded video data generated by source device 102. Destination device 116 may access stored video data from file server 114 via streaming or download.

File server 114 may be any type of server device that may store encoded video data and transmit the encoded video data to destination device 116. File server 114 may be a web server (e.g., for a website), a server configured to provide file transfer protocol services (such as the File Transfer Protocol (FTP) or the File Delivery over Unidirectional Transport (FLUTE) protocol), or a content delivery network. (CDN) device, Hypertext Transfer Protocol (HTTP) server, Multimedia Broadcast Multicast Service (MBMS) or Enhanced MBMS (eMBMS) server, and/or Network Attached Storage (NAS) device. File server 114 may additionally or alternatively implement one or more HTTP streaming protocols, such as Dynamic Adaptive Streaming over HTTP (DASH), HTTP Live Streaming (HLS), Real Time Streaming Protocol (RTSP), HTTP Dynamic Streaming, etc. It may be possible.

Destination device 116 may access encoded video data from file server 114 via any standard data connection, including an Internet connection. This is suitable for accessing encoded video data stored on file server 114, over a wireless channel (e.g., Wi-Fi connection), a wired connection (e.g., Digital Subscriber Line (DSL), cable modem, etc.), or both. It may include a combination of all of them. Input interface 122 is configured to operate in accordance with any one or more of the various protocols discussed above for retrieving or receiving media data from file server 114, or other such protocols for retrieving media data. It could be.

Output interface 108 and input interface 122 may include wireless transmitters/receivers, modems, wired networking components (e.g., Ethernet cards), wireless communication components operating in accordance with any of the various IEEE 802.11 standards. , or may represent other physical components. In examples where output interface 108 and input interface 122 include wireless components, output interface 108 and input interface 122 may be configured to support a wireless network such as 4G, 4G-LTE (Long Term Evolution), LTE Advanced, 5G, etc. Depending on cellular communication standards, it may be configured to transmit data, such as encoded video data. In some examples where output interface 108 includes a wireless transmitter, output interface 108 and input interface 122 may be configured to comply with other wireless standards, such as the IEEE 802.11 specification, IEEE 802.15 specification (e.g., ZigBee™), Bluetooth™ standard, etc. Depending on the device, it may be configured to transmit data such as encoded video data. In some examples, source device 102 and/or destination device 116 may include separate system-on-chip (SoC) devices. For example, source device 102 may include a SoC device to perform functions due to video encoder 200 and/or output interface 108, and destination device 116 may include video decoder 300. and/or a SoC device to perform functions due to input interface 122.

The techniques of this disclosure include over-the-air television broadcasts, cable television transmissions, satellite television transmissions, Internet streaming video transmissions, such as dynamic adaptive streaming over HTTP (DASH), and data storage. It may be applied to video coding to support any of a variety of multimedia applications, such as digital video encoded on a medium, decoding of digital video stored on a data storage medium, or other applications.

Input interface 122 of destination device 116 receives an encoded video bitstream from computer-readable medium 110 (e.g., communication medium, storage device 112, file server 114, etc.). The encoded video bitstream consists of syntax elements having values that describe the processing and/or characteristics of video blocks or other coded units (e.g., slices, pictures, groups of pictures, sequences, etc.) The same may include signaling information defined by video encoder 200 that is also used by video decoder 300. Display device 118 displays decoded pictures of the decoded video data to the user. Display device 118 may represent any of a variety of display devices, such as a liquid crystal display (LCD), plasma display, organic light-emitting diode (OLED) display, or other type of display device.

Although not shown in FIG. 1 , in some examples, video encoder 200 and video decoder 300 may be integrated with an audio encoder and/or an audio decoder, respectively, in a common data stream. It may also include appropriate MUX-DEMUX units, or other hardware and/or software, to handle multiplexed streams containing both audio and video.

Video encoder 200 and video decoder 300 each may include a variety of suitable encoder and/or decoder circuitry, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), and field programmable. It may be implemented as any of gate arrays (FPGAs), discrete logic, software, hardware, firmware, or any combinations thereof. If the techniques are implemented in part in software, the device may store instructions for the software in a suitable, non-transitory computer-readable medium and execute the instructions in hardware using one or more processors to perform the techniques of the present disclosure. there is. Each of video encoder 200 and video decoder 300 may be included in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (CODEC) in a separate device. . A device comprising video encoder 200 and/or video decoder 300 may include an integrated circuit, a microprocessor, and/or a wireless communication device, such as a cellular telephone.

Video encoder 200 and video decoder 300 support video coding standards such as ITU-T H.265, also referred to as High Efficiency Video Coding (HEVC), or extensions thereof, such as multi-view and/or scalable video. It may also operate depending on coding extensions. Alternatively, video encoder 200 and video decoder 300 may operate according to other proprietary or industry standards, such as ITU-T H.266, also referred to as Versatile Video Coding (VVC). In other examples, video encoder 200 and video decoder 300 may encode data according to a proprietary video codec/format, such as AOMedia Video 1 (AV1), extensions of AV1, and/or successor versions of AV1 (e.g., AV2). It might work. In other examples, video encoder 200 and video decoder 300 may operate according to other proprietary formats or industry standards. However, the techniques of this disclosure are not limited to any particular coding standard or format. In general, video encoder 200 and video decoder 300 may be configured to perform the techniques of this disclosure along with any video coding techniques that use motion vector difference sign prediction.

In general, video encoder 200 and video decoder 300 may perform block-based coding of pictures. The term “block” generally refers to a structure containing data to be processed (eg, to be encoded, decoded, or otherwise used in an encoding and/or decoding process). For example, a block may include a two-dimensional matrix of samples of luminance and/or chrominance data. In general, video encoder 200 and video decoder 300 may code video data represented in YUV (e.g., Y, Cb, Cr) format. That is, rather than coding red, green, and blue (RGB) data for samples of a picture, video encoder 200 and video decoder 300 may code luminance and chrominance components, where Minance components may include both red tint and blue tint chrominance components. In some examples, video encoder 200 converts received RGB formatted data to a YUV representation prior to encoding, and video decoder 300 converts the YUV representation to an RGB format. Alternatively, pre- and post-processing units (not shown) may perform these transformations.

This disclosure may generally refer to coding of pictures (e.g., encoding and decoding), which includes the process of encoding or decoding data of a picture. Similarly, this disclosure may refer to coding of blocks of a picture, including processes for encoding or decoding data for the blocks, such as prediction and/or residual coding, for example. An encoded video bitstream typically contains a set of values for syntax elements that indicate coding decisions (e.g., coding modes) and partitioning of pictures into blocks. Accordingly, references to coding a picture or block should generally be understood as coding values for syntax elements that form the picture or block.

HEVC defines various blocks including coding units (CUs), prediction units (PUs), and transform units (TUs). According to HEVC, a video coder (e.g., video encoder 200) partitions a coding tree unit (CTU) into CUs according to a quadtree structure. That is, the video coder partitions the CTUs and CUs into four identical, non-overlapping squares, and each node of the quadtree has 0 or 4 child nodes. Nodes without child nodes may be referred to as “leaf nodes,” and the CUs of such leaf nodes may include one or more PUs and/or one or more TUs. The video coder may further partition PUs and TUs. For example, in HEVC, the residual quadtree (RQT) represents the partitioning of TUs. In HEVC, PUs represent inter-prediction data, while TUs represent residual data. Intra-predicted CUs contain intra-prediction information, such as an intra-mode indication.

As another example, video encoder 200 and video decoder 300 may be configured to operate in accordance with VVC. According to VVC, a video coder (e.g., video encoder 200) partitions a picture into a plurality of coding tree units (CTUs). Video encoder 200 may partition CTUs according to a tree structure, such as a quadtree binary tree (QTBT) structure or a multi-type tree (MTT) structure. The QTBT structure eliminates the concept of multiple partition types, such as the separation between CUs, PUs, and TUs in HEVC. The QTBT structure includes two levels: a first level partitioned according to quadtree partitioning, and a second level partitioned according to binary tree partitioning. The root node of the QTBT structure corresponds to CTU. Leaf nodes of binary trees correspond to coding units (CUs).

In the MTT partitioning structure, blocks are partitioned using quadtree (QT) partitions, binary tree (BT) partitions, and one or more types of triple tree (TT) (also referred to as ternary tree (TT)) partitions. It can also be partitioned. A triple or ternary tree partition is a partition in which a block is divided into three subblocks. In some examples, a triple or ternary tree partition splits a block into three subblocks without splitting the original block through its center. Partitioning types in MTT (eg, QT, BT, and TT) may be symmetric or asymmetric.

When operating according to the AV1 codec, video encoder 200 and video decoder 300 may be configured to code video data into blocks. In AV1, the largest coding block that can be processed is referred to as a superblock. In AV1, a superblock can be either 128x128 luma samples or 64x64 luma samples. However, in subsequent video coding formats (eg, AV2), a superblock may be defined by different (eg, larger) luma sample sizes. In some examples, a superblock is the top level of a block quadtree. Video encoder 200 may further partition the superblock into smaller coding blocks. Video encoder 200 may partition superblocks and other coding blocks into smaller blocks using square or non-square partitioning. Non-square blocks may include N/2xN, NxN/2, N/4xN, and NxN/4 blocks. Video encoder 200 and video decoder 300 may perform separate prediction and transform processes for each of the coding blocks.

AV1 also defines tiles of video data. A tile is a rectangular array of superblocks that can be coded independently from other tiles. That is, video encoder 200 and video decoder 300 may each encode and decode coding blocks within a tile without using video data from other tiles. However, video encoder 200 and video decoder 300 may perform filtering across tile boundaries. Tiles may or may not be uniform in size. Tile-based coding may enable parallel processing and/or multi-threading for encoder and decoder implementations.

In some examples, video encoder 200 and video decoder 300 may use a single QTBT or MTT structure to represent each of the luminance and chrominance components, while in other examples, video encoder 200 and video decoder 300 configures one QTBT/MTT structure for a luminance component and another QTBT/MTT structure for both chrominance components (or two QTBT/MTT structures for individual chrominance components). ) You can also use two or more QTBT or MTT structures, such as

Video encoder 200 and video decoder 300 may be configured to use quadtree partitioning, QTBT partitioning, MTT partitioning, superblock partitioning, or other partitioning structures.

In some examples, a CTU is a coding tree block (CTB) of luma samples, two corresponding CTBs of chroma samples of a picture with three sample arrays, or three separate color planes used to code the samples, and Contains the CTB of samples of a picture or monochrome picture that is coded using syntax structures.　 A CTB may be an NxN block of samples for some value of N such that the division of a component into CTBs is partitioned.　 A component is an array or a single sample from one of three arrays (luma and two chroma) that make up a picture in 4:2:0, 4:2:2, or 4:4:4 color format, or monochrome format. It is an array of arrays or single samples that make up a picture.　 In some examples, a coding block is an MxN block of samples for some values of M and N such that the division of the CTB into coding blocks is partitioned.　

Blocks (eg, CTUs or CUs) may be grouped in various ways in a picture. As an example, a brick may refer to a rectangular area of CTU rows within a specific tile in a picture. A tile may be a rectangular area of CTUs within a specific tile row and a specific tile row in a picture. A tile row refers to a rectangular area of CTUs with a height equal to the height of the picture and a width specified by syntax elements (e.g., as in a picture parameter set). A tile row refers to a rectangular region of CTUs with a width equal to the width of the picture and a height specified by syntax elements (e.g., as in a picture parameter set).

In some examples, a tile may be partitioned into multiple bricks, each of which may contain one or more CTU rows within the tile. A tile that is not partitioned into multiple bricks may also be referred to as a brick. However, bricks that are a true subset of tiles may not be referred to as tiles. Bricks in a picture may also be arranged into slices. A slice may be an integer number of bricks of a picture that may be contained exclusively in a single network abstraction layer (NAL) unit. In some examples, a slice contains only a contiguous sequence of multiple complete tiles or complete bricks of one tile.

This disclosure may use “NxN” and “N by N” interchangeably to refer to the sample dimensions of a block (such as a CU or other video block) in terms of vertical and horizontal dimensions, e.g., 16x16 samples. Or 16 by 16 samples. Typically, a 16x16 CU will have 16 samples in the vertical direction (y = 16) and 16 samples in the horizontal direction (x = 16). Likewise, an NxN CU will generally have 16 samples in the vertical direction (y = 16). With N samples and N samples in the horizontal direction, where N represents a non-negative integer value, the samples in a CU may be arranged in rows and columns. Moreover, the CUs may have the same number of samples as in the vertical direction. For example, CUs may contain N×M samples, where M is not necessarily equal to N.

Video encoder 200 encodes video data for CUs that represent prediction and/or residual information, and other information. Prediction information indicates how the CU will be predicted to form a prediction block for the CU. Residual information generally represents sample-by-sample differences between samples of a CU before encoding and a prediction block.

To predict a CU, video encoder 200 may form a prediction block for the CU, generally through inter-prediction or intra-prediction. Inter prediction generally refers to predicting a CU from data in a previously coded picture, while intra prediction generally refers to predicting a CU from previously coded data in the same picture. To perform inter prediction, video encoder 200 may use one or more motion vectors to generate a prediction block. Video encoder 200 may perform a motion search to identify a reference block that closely matches a CU, generally in terms of differences between the CU and the reference block. The video encoder 200 can encode sum of absolute differences (SAD), sum of squared differences (SSD), mean absolute difference (MAD), and mean squared differences. differences; MSD), or other such difference calculations to determine whether a reference block closely matches the current CU. In some examples, video encoder 200 may predict the current CU using one-way prediction or two-way prediction.

Some examples of VVC also provide an affine motion compensation mode, which may be considered an inter-prediction mode. In an affine motion compensation mode, video encoder 200 may determine two or more motion vectors that represent non-translational motion, such as zooming in or out, rotation, perspective motion, or other irregular motion types.

To perform intra prediction, video encoder 200 may select an intra prediction mode to generate a prediction block. Some examples of VVC provide 67 intra-prediction modes, including planar mode and DC mode as well as various directional modes. In general, video encoder 200 selects an intra-prediction mode that describes neighboring samples for a current block (e.g., a block of a CU) from which to predict samples of the current block. Such samples are generally in the same picture as the current block, assuming that video encoder 200 codes the CTUs and CUs in raster scan order (left to right, top to bottom). and on the left side, or may be on the left side.

Video encoder 200 encodes data indicating the prediction mode for the current block. For example, for inter-prediction modes, video encoder 200 may encode data indicating which of the various available inter-prediction modes is used, as well as motion information for the corresponding mode. For one-way or two-way inter-prediction, for example, video encoder 200 may encode motion vectors using advanced motion vector prediction (AMVP) or merge mode. Video encoder 200 may encode motion vectors for an affine motion compensation mode using similar modes.

AV1 includes two general techniques for encoding and decoding coding blocks of video data. Two common techniques are intra prediction (eg, intra frame prediction or spatial prediction) and inter prediction (eg, inter frame prediction or temporal prediction). In the context of AV1, when predicting blocks of the current frame of video data using intra prediction mode, video encoder 200 and video decoder 300 do not use video data from other frames of video data. For most intra prediction modes, video encoder 200 encodes blocks of the current frame based on the difference between sample values in the current block and predicted values generated from reference samples in the same frame. Video encoder 200 determines predicted values generated from reference samples based on intra prediction mode.

Following prediction, such as intra-prediction or inter-prediction of a block, video encoder 200 may calculate residual data for the block. Residual data, such as a residual block, represents sample-by-sample differences between a block and a prediction block for that block, formed using a corresponding prediction mode. Video encoder 200 may apply one or more transforms to the residual block to generate transformed data in the transform domain instead of the sample domain. For example, video encoder 200 may apply a discrete cosine transform (DCT), integer transform, wavelet transform, or conceptually similar transform to the residual video data. Additionally, video encoder 200 may apply a secondary transform following the first transform, such as a mode-dependent non-separable secondary transform (MDNSST), signal dependent transform, Karhunen-Loeve transform (KLT), etc. Video encoder 200 generates transform coefficients following application of one or more transforms.

As mentioned above, following any transforms to generate transform coefficients, video encoder 200 may perform quantization of the transform coefficients. Quantization generally refers to a process in which transform coefficients are quantized to possibly reduce the amount of data used to represent the transform coefficients, thereby providing additional compression. By performing a quantization process, video encoder 200 may reduce the bit depth associated with some or all of the transform coefficients. For example, video encoder 200 may round down an n-bit value to an m-bit value during quantization, where n is greater than m. In some examples, to perform quantization, video encoder 200 may perform a bitwise right-shift of the value to be quantized.

Following quantization, video encoder 200 may scan the transform coefficients to generate a one-dimensional vector from a two-dimensional matrix containing the quantized transform coefficients. The scan may be designed to place higher energy (and therefore lower frequency) transform coefficients in front of the vector and place lower energy (and therefore higher frequency) transform coefficients behind the vector. In some examples, video encoder 200 may utilize a predefined scan order to scan the quantized transform coefficients to generate a serialized vector and then entropy encode the quantized transform coefficients of the vector. In other examples, video encoder 200 may perform adaptive scan. After scanning the quantized transform coefficients to form a one-dimensional vector, video encoder 200 may entropy encode the one-dimensional vector, for example, according to context-adaptive binary arithmetic coding (CABAC). Video encoder 200 may also entropy encode values for syntax elements that describe metadata associated with encoded video data for use by video decoder 300 in decoding the video data.

To perform CABAC, video encoder 200 may assign a context within a context model to the symbol to be transmitted. Context may relate to, for example, whether a symbol's neighboring values are zero values. The probability determination may be based on the context assigned to the symbol.

Video encoder 200 may transmit syntax data, such as block-based syntax data, picture-based syntax data, and sequence-based syntax data, to video decoder 300, e.g., as a picture header, block header, slice header, or other syntax. Data may additionally be generated, such as a sequence parameter set (SPS), a picture parameter set (PPS), or a video parameter set (VPS). Video decoder 300 may similarly decode such syntax data to determine how to decode the corresponding video data.

In this way, video encoder 200 generates syntax elements that describe the partitioning of encoded video data, e.g., a picture, into blocks (e.g., CUs) and prediction and/or residual information for the blocks. You can also create a bitstream containing Ultimately, video decoder 300 may receive the bitstream and decode the encoded video data.

In general, video decoder 300 performs a process reversible to that performed by video encoder 200 to decode encoded video data in a bitstream. For example, video decoder 300 may decode values for syntax elements of a bitstream using CABAC in a manner substantially similar to the CABAC encoding process of video encoder 200 but reversible. Syntax elements may define partitioning information for partitioning of a picture into CTUs and partitioning of each CTU according to a corresponding partition structure, such as a QTBT structure, thereby defining CUs of the CTU. Syntax elements may further define prediction and residual information for blocks (eg, CUs) of video data.

Residual information may be represented by, for example, quantized transform coefficients. Video decoder 300 may inverse quantize and inverse transform the quantized transform coefficients of a block to reproduce the residual block for the block. Video decoder 300 uses the signaled prediction mode (intra- or inter-prediction) and associated prediction information (e.g., motion information for inter-prediction) to form a prediction block for the block. Video decoder 300 may then combine the prediction block and the residual block (on a per-sample basis) to reproduce the original block. Video decoder 300 may perform additional processing, such as performing a deblocking process to reduce visual artifacts along the boundaries of a block.

This disclosure may generally refer to “signaling” certain information, such as syntax elements. The term “signaling” generally refers to values for syntax elements used to decode encoded video data, and/ Or, it may refer to communication of other data. That is, video encoder 200 may signal values for syntax elements in a bitstream. Signaling generally refers to generating values in a bitstream. As noted above, source device 102 may store the bitstream in non-real-time or substantially real-time, as may occur when storing syntax elements in storage device 112 for later retrieval by destination device 116. may be transmitted to the destination device 116.

The techniques of this disclosure relate to inter prediction and inter-related information coding. More specifically, this disclosure describes a method and device for predicting the sign (e.g., polarity) of a motion vector difference (MVD). The techniques of this disclosure apply to extensions of any of the existing video codecs, such as High Efficiency Video Coding (HEVC), and/or Versatile Video Coding (and/or VVC), Essential Video Coding (EVC), or to future video coding. It may be an efficient coding tool in coding standards.

As described in more detail below, according to the techniques of this disclosure, video decoder 300 uses the possible sign values, respective magnitudes of the motion vector difference coordinates, and a motion vector predictor for a block of video data. Constructing motion vector candidates, wherein possible sign values include positive sign values and negative sign values; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine a motion vector difference sign based on the motion vector sign predictor index and the sorted list; and decode the block of video data using the magnitudes of the motion vector difference coordinates and the motion vector difference sign.

In the following sections, work in HEVC, JEM techniques, and VVC related to the techniques of this disclosure is reviewed.

MVD code coding of VVC

In VVC and Enhanced Compression Model (ECM) software currently in development, a video encoder (e.g., video encoder 200) converts the motion vector difference (MVD) of the bitstream to a video decoder (e.g., video encoder 200). It may be configured to signal to the decoder 300. MVD is the difference between the motion vector (MV) used to derive the inter predictor and the corresponding motion vector predictor (MVP). MV, MVP, and MVD are vectors and have two components: a horizontal component (x) and a vertical component (y). When MVDx or MVDy is not equal to 0, video encoder 200 may signal the sign of the component (e.g., a syntax element indicating positive polarity or negative polarity). In some examples, the sign is signaled using CABAC bypass mode (e.g., coded with a fixed probability model rather than context coded).

Affine motion prediction in VVC

In HEVC, only translational motion models are used for motion compensation prediction (MCP). In some examples, translational motion models are used with so-called “regular inter prediction”. In the real world, there are various types of motion, not just linear translational motion. Other types of motion may include zooming, rotation, perspective motion, and other irregular motions. In VVC, simplified affine transform motion compensation prediction can be used to improve coding efficiency. 2 is a conceptual diagram illustrating an example simplified affine motion model. As shown in Figure 2, the affine motion field of current block 400 is described by control point motion vectors 402 (v ₀ ) and 404 (v ₁ ). In another example, three control point motion vectors may be used to define motion.

For example, using an affine motion model with two control point motion vectors, the motion vector field (MVF) of a block is described by the following equation:

Here, ( v _0x , v _0y ) is the motion vector of the upper left corner control point, and ( v _1x , v _1y ) is the motion vector of the upper right corner control point.

Merge Mode with MVD (MMVD)

In VVC and ECM, in addition to the merge mode in which implicitly derived motion information is used directly for prediction sample generation of the current CU, the merge mode with motion vector differences (MMVD) mode can also be used. Video encoder 200 may signal the MMVD flag after sending the regular merge flag to specify whether MMVD mode is used for the CU.

In MMVD, after a merge candidate is selected, the merge candidate is further refined by signaled MVD information. Merge candidates include motion information of neighboring blocks of the currently coded block. A video decoder may be configured to construct a list of merge candidates and may select motion information associated with a merge candidate indicated by the video encoder (e.g., by a merge index for the candidate list). Motion information may include a motion vector, reference picture list, and prediction direction.

The signaled MVD information includes an MMVD candidate flag, an index specifying the motion magnitude, and an index indicating the motion direction. In MMVD mode, one of the first two candidates in the merge list is selected to be used as the starting MV. The MMVD candidate flag is signaled to specify which merge candidate is used between the first merge candidate and the second merge candidate.

3 is a conceptual diagram illustrating example MMVD search points. In Figure 3, position 410 is the position pointed to by the starting motion vector. For each of the reference lists L0 and L1, positions 412 and 414 are determined by adding a positive or negative offset, respectively, to the x coordinate of the starting motion vector. Positions 416 and 418 are determined by adding a positive or negative offset, respectively, to the y coordinate of the starting motion vector. The other positions shown in Figure 3 are determined in a similar manner, but using a larger offset.

The distance index (distance IDX) specifies motion magnitude information and indicates a predefined offset from the starting point. As shown in Figure 3, an offset is added to the horizontal or vertical component of the starting MV. An example of the relationship between distance index and predefined offset is specified in Table 1.

Table 1 - Relationship between distance indices and predefined offsets Distance IDX 0 One 2 3 4 5 6 7 Offset (in units of luma samples) 1/4 1/2 One 2 4 8 16 32

The direction index (direction IDX) indicates the direction of the MVD with respect to the starting point (e.g., positive or negative sign for magnitude). The direction index may represent one of the four directions shown in Table 2 below. Note that the meaning of the MVD code is variable depending on the information of the starting MVs. If the starting MVs are single-predicted MVs or dual-predicted MVs, and both lists point to the same side of the current picture (e.g., the picture order count (POC) of the two references is the POC of the current picture) are both greater than or are both less than the POC of the current picture), the sign in Table 2 specifies the sign of the MV offset added to the start MV.

Bi-predictive MVs are where the starting MVs are two MVs that point to different sides of the current picture (e.g., the POC of one reference is larger than the POC of the current picture, and the POC of the other reference is smaller than the POC of the current picture) , when the difference in the POC of list 0 is greater than the POC of list 1, the sign in Table 2 specifies the sign of the MV offset added to the list0 MV component of the starting MV and the sign for list1 MV has the opposite value. Otherwise, if the difference between the POC of list 1 is greater than that of list 0, the sign in Table 2 specifies the sign of the MV offset added to the list1 MV component of the starting MV, and the sign of list0 MV has the opposite value.

MVD is scaled according to the POC difference in each direction. If the difference between the POCs of the two lists is the same, scaling is not necessary. Otherwise, if the POC difference in list 0 is greater than the POC in list 1, the MVD for list 1 is scaled by defining the POC difference in L0 as the variable td and the POC difference in L1 as the variable tb. If the POC difference in L1 is greater than L0, the MVD of list 0 is scaled in the same way. If the starting MV is a single prediction, the MVD is added to the available MVs.

Table 2 - Sign of MV offset specified by direction index Direction IDX 00 01 10 11 x-axis + - N/A N/A y-axis N/A N/A + -

Affine MMVD

In ECM, MMVD may be further extended and applied in an affine inter prediction mode. In affine MMVD, as in regular inter MMVD, four directions are used to determine the MVD sign of each component of the MVD, and the corresponding MVD sign and direction index table are shown in Table 2 above. However, affine inter prediction uses two or three control point motion vectors to determine the motion model of a single prediction direction, so the same MVD is added to all control point motion vectors (CPMV) to reduce complexity. In the case of bi-prediction, if two reference pictures are temporally located before or after the current picture to be coded, the MVD used for the two reference lists will be the same. If two reference pictures are located on different sides in time relative to the current picture, an MVD with an opposite value is added to CPMV from reference list 1.

Geometric Partitioning Mode (GPM) with MMVD

In VVC, geometric partitioning mode is supported for inter prediction. Geometric partitioning mode is a type of merge mode and is signaled using a CU-level flag, and other merge modes include regular merge mode, MMVD mode, combined inter/intra prediction (CIIP) mode and subblock merge mode. A total of 64 partitions are supported by GPM for each possible CU size as follows: wxh = 2 ^m x 2 ⁿ with m, n ∈ {3...6}, excluding 8x64 and 64x8.

Figure 4 is a conceptual diagram showing an example of GPM segments 430 grouped at the same angle. When GPM is used, the CU is divided into two parts by a geometrically positioned straight line (see Figure 4). The position of the dividing line is derived mathematically from the angle and offset parameters of the specific partition. Each part of the geometric partition in the CU is inter-predicted using its own motion information. In one example, only a single prediction is allowed for each partition. For example, each partition has one motion vector and one reference index. A one-way-prediction motion constraint is applied to ensure that only two motion compensated predictions are needed for each CU, as in conventional two-way prediction.

If a geometric partitioning mode is used for the current CU, a geometric partition index indicating the partition mode (angle and offset) of the geometric partition, and two merge indices (one for each partition) are additionally signaled. The maximum GPM candidate size is explicitly signaled in the SPS and specifies the syntax binarization for GPM merge indices. After predicting each part of the geometric partition, sample values along the geometric partition edges are adjusted using blending processing with adaptive weights. This is the prediction signal for the entire CU, and the transform and quantization process will be applied to the entire CU as in other prediction modes.

In one example of ECM, GPM is further extended by applying motion vector refinement on top of the existing GPM unidirectional MV. A flag on the GPM CU is first signaled to specify whether this motion vector refinement mode is used. When motion vector refinement mode is used, video encoder 200 may determine whether to signal an MVD for each geometric partition of a GPM CU. If MVD is signaled for a geometric partition, after the GPM merge candidate is selected, the motion of the partition is further refined by the signaled MVD information. All other procedures remain the same as in GPM.

MVD is signaled as a pair of distance and direction, similar to MMVD. GPM with MMVD (GPM-MMVD) contains 9 candidate distances (¼ pixel, ½ pixel, 1 pixel, 2 pixels, 3 pixels, 4 pixels, 6 pixels, 8 pixels, 16 pixels) and 8 candidate directions ( There are 4 horizontal/vertical directions and 4 diagonal directions).

Multiple Hypothesis Prediction (MHP)

Multi-hypothesis inter prediction mode (e.g. M. Winken, et. al. “CE10: Multi-hypothesis inter prediction (Test 10.1.2),” Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11, 13 ^th Meeting: Marrakech, MA, 9-18 January 2019, JVET-M0425), one or more additional motion compensation prediction signals are signaled in addition to the existing bidirectional prediction signals. The resulting overall prediction signal is obtained through sample-wise weighted superposition. Using the bidirectional prediction signal p _bi and the first additional inter prediction signal/hypothesis h ₃ , the resulting prediction signal p ₃ is obtained as follows:

The weight factor α is specified by the syntax element add_hyp_weight_idx according to the following mapping:

Similar to the above technique, two or more additional prediction signals may be used. The resulting overall prediction signal is iteratively accumulated with each additional prediction signal.

The resulting overall prediction signal is obtained as the last p _n (e.g., p _n with maximum index n). In one example, up to two additional prediction signals may be used (e.g., n is limited to 2).

The motion parameters of each additional prediction hypothesis can be signaled explicitly by specifying the reference index, motion vector predictor index, and motion vector difference, or implicitly by specifying the merge index. A separate multi-hypothesis merge flag may be used to distinguish between these two signaling modes.

In one example, for inter AMVP mode, MHP is applied only when unequal weights of bidirectional prediction using CU-level weighting (BCW) mode are selected in bidirectional prediction mode.

A combination of MHP and bidirectional optical flow (BDOF) coding is possible. However, in one example, BDOF applies only to the bidirectional prediction signal portion of the prediction signal (e.g., the first two hypotheses in general).

12-tap interpolation filter

In this example, the 8-tap interpolation filter used in VVC is replaced with a 12-tap filter. The 12-tap interpolation filter is derived from a sinc function, the frequency response of which is cut off at the Nyquist frequency and truncated by a cosine window function. Table 3 provides filter coefficients for all 16 phases. Figure 5 shows a graph 440 comparing the frequency response of a 12-tap interpolation filter (filter response A) with a VVC interpolation filter (filter response B), all in half-pixel phase.

Table 3. Filter coefficients of 12-tap interpolation filter. 1/16 -One 2 -3 6 -14 254 16 -7 4 -2 One 0 2/16 -One 3 -7 12 -26 249 35 -15 8 -4 2 0 3/16 -2 5 -9 17 -36 241 54 -22 12 -6 3 -One 4/16 -2 5 -11 21 -43 230 75 -29 15 -8 4 -One 5/16 -2 6 -13 24 -48 216 97 -36 19 -10 4 -One 6/16 -2 7 -14 25 -51 200 119 -42 22 -12 5 -One 7/16 -2 7 -14 26 -51 181 140 -46 24 -13 6 -2 8/16 -2 6 -13 25 -50 162 162 -50 25 -13 6 -2 9/16 -2 6 -13 24 -46 140 181 -51 26 -14 7 -2 10/16 -One 5 -12 22 -42 119 200 -51 25 -14 7 -2 11/16 -One 4 -10 19 -36 97 216 -48 24 -13 6 -2 12/16 -One 4 -8 15 -29 75 230 -43 21 -11 5 -2 13/16 -One 3 -6 12 -22 54 241 -36 17 -9 5 -2 14/16 0 2 -4 8 -15 35 249 -26 12 -7 3 -One 15/16 0 One -2 4 -7 16 254 -14 6 -3 2 -One

Template Matching Prediction (TMP)

Template matching (TM) prediction is a special merging mode based on frame rate up conversion (FRUC) techniques. In one example TM mode, the motion information of the block is not signaled, but is derived in video decoder 300. TM may apply to both AMVP mode and regular merge mode. In AMVP mode, MVP candidate selection is determined based on template matching to select a candidate that reaches the minimum difference between the current block template and the reference block template. For regular merge mode, the TM mode flag is signaled to indicate use of the TM, and then the TM is applied to the merge candidates indicated by the merge index for MV refinement.

6 is a conceptual diagram illustrating an example of template matching performed on a search area around an initial motion vector. As shown in Figure 6, template matching is the closest match between the top template 452 and the left template 454 (top and/or left neighboring blocks of the current CU 450) in the current picture 460. It is used to derive motion information of the current CU 450 by discovering . With an AMVP candidate selected based on the initial matching error, its MVP is refined by template matching. With the merge candidate indicated by the signaled merge index, L0 and its merged MVs corresponding to L1 are independently refined by template matching, and then the less accurate candidates are further merged back into better candidates as priors. It is refined.

Cost function: If the motion vector points to fractional sample positions, motion compensated interpolation is used. To reduce complexity, bi-linear interpolation instead of 8-tap DCT-IF interpolation may be used for template matching to generate templates on reference pictures. The matching cost (C) of template matching is calculated as follows:

and

where w is a weighting factor that is empirically set to 4, and MV and MV ^s represent the currently testing MV and initial MV (e.g., MVP candidate in AMVP mode or merged motion in merge mode), respectively. The sum of absolute differences (SAD) is used as the matching cost for template matching. In one example, when TM is used, motion is refined by using only luma samples. The derived motion will be used for both luma and chroma for motion compensated inter prediction. After the MV is determined, final motion compensation is performed using an 8-tap interpolation filter for luma and a 4-tap interpolation filter for chroma.

Search method: MV refinement is a pattern-based MV search based on template matching cost and hierarchical structure. Two search patterns are supported - diamond search and cross search for MV refinement. The hierarchical structure specifies an iterative process for refining the MV, starting at coarse MVD precision (eg, 1/4-pel) and ending at fine precision (eg, 1/8-pel). MV is retrieved directly with 1/4 luma sample MVD precision into the diamond pattern, followed by 1/4 luma sample MVD precision into the cross pattern. This is followed by 1/8 luma sample MVD purification in a cross pattern. The search range of MV purification is set equal to (-8, +8) luma samples around the initial MV. When the current block is coded using bi-prediction, the MVs quantum modes are refined independently, and then the best of them (in terms of matching cost) is added to the other MVs with BCW weight values. It is set up as a fryer for purification.

MVD sign prediction

MVD sign prediction can be used to derive a specific cost given a hypothetical MVD and output the correct MVD sign predictor index by comparing the actual MVD with a list of MVD candidates sorted by cost. In this way, instead of directly signaling the MVD sign in equal probability (EP) coding mode (e.g., bypass mode), the correct MVD sign (e.g., the sign for the x and/or y components of the MVD) is used. The representing MVD code predictor index is coded into the context model. Converting from EP coding to context-based coding is one source of benefit. Given an example of deriving the cost based on the current and reference templates, the decoder side MVD code is derived by applying the following steps:

1) Generate a list of MVD candidates based on the absolute values of the MVD components (4 candidates if both the X and Y components of the MVD are non-zero, 2 candidates if one component is 0);

2) Calculate the cost for each MVD candidate using template matching;

3) Sort and rank MVD candidates based on their calculated costs;

4) Determine the MVD and associated sign of the sorted list according to the MVD index obtained from the bitstream (e.g., the MVD index for the sorted MVD candidate list, for which the MVD index is signaled by the video encoder).

The template matching cost is measured using a specific metric between the current CU's template and its reference template. An example of the MVD code prediction process using template matching is shown in Figure 7. MVD sign prediction can be applied not only to transform blocks but also to affine blocks.

In Figure 7, the motion vector predictor (MVP) 472 of block 470 points to a specific location of the reference picture. Possible MVD candidates include MVD candidates A, B, C, and D. MVD candidates include the MVD size and sign. The four MVD candidates are offset from the position indicated by MVP 472. The cost is determined for each of the four MVD candidates using the top and left templates 474, 476, 478 and 480.

This disclosure describes a technique in which MVD sign prediction applies not only to regular inter and affine inter modes in which the MVD is explicitly signaled, but also to the MMVD mode and other modes in which the MVD is determined from the direction index and from the step size representing the MVD size. Explain. As described above, the direction index specifies the direction of the MVD, which is the same as specifying the sign of the non-zero MVD component. This disclosure describes a technique where the direction index does not need to be signed, but rather the MVD code can be predicted using the MVD code prediction technique described below. With the introduction of new coding tools in ECM and MVD, the sign prediction techniques of this disclosure can be further extended to several new coding tools such as affine MMVD, GPM MMVD and MHP, as discussed below.

MMVD direction/sign prediction for MMVD

Video decoder 300 may decode an MMVD step index (e.g., representing MVD size information), and subsequently video decoder 300 may use the already decoded MVD size information to determine the MMVD direction (e.g., MVD size information) of this disclosure. For example, sign) prediction may be performed. As described above, video decoder 300 may be configured to determine MVD size information from an MMVD step index (e.g., distance IDX in Table 1).

Depending on the POC distance between the current picture and two reference pictures, video decoder 300 may apply MVD scaling to the MVD size after the MVD size is derived using the step index. Note that although a single MVD size can be derived, the derived MVD size can be applied to each individual component of the MVD (e.g., x component and y component). In this way, the MVD size information described in this specification may mean the size of each motion vector difference component.

Deriving the MVD code is equivalent to deriving the direction index of the signaled MMVD direction index. Unlike regular inter mode and affine inter mode where it is known whether the x or y MVD component is non-zero, the MMVD direction index in MMVD mode specifies one zero component and one non-zero component. For example, the x component of an MVD is nonzero and the y component is 0, and vice versa. Therefore, when performing MMVD direction prediction, which MVD components are non-zero and their associated signs remain unknown. Therefore, MMVD direction prediction can be jointly applied to both MVD components, and the MMVD sign predictor index determines which component is the non-zero component in the MVD as well as the sign information.

The video decoder 300 determines the MMVD sign prediction by generating a template using the MV derived by adding all possible MVDs containing different signs and non-zero positions to MVP and deriving a template matching cost. In MMVD, MVP may be indicated by a merge index. In the current example MMVD design, a total of four different MVDs may be used, and thus four different final MVs may be generated from the motion vector candidate list. As an example, from the decoded MMVD step index, video decoder 300 determines that the MVD size is 16. The video decoder constructs motion vector candidates using all possible sign values (e.g., positive or negative for each MVD component as in Table 2 above). In this example, the motion vector candidates are (16, 0), (-16, 0), (0, 16), (0, -16).

In one example, the template size of the current block used to determine cost is fixed to the given block coordinates. However, the reference template location varies due to the existence of multiple possible final MVs (eg, a list of motion vector candidates). The corresponding reference template can be derived using each of the MV candidates in the list. Video decoder 300 may then use certain measurements or metrics to derive a cost when comparing the current template to a reference template. In one example, video decoder 300 may calculate the cost as the sum of absolute differences (SAD). Other metrics such as sum of squared errors (SSE) or any other power can also be used.

After the cost for each possible candidate motion vector is derived, the candidate motion vectors are sorted based on the derived template matching cost. Video decoder 300 decodes an MMVD direction predictor index from the encoded video bitstream that indicates where in the sorted list the actual MVD is located. In one example, the MMVD direction predictor index is signaled in a context coded bin. Therefore, the actual final MV can be reconstructed by deriving the actual MVD with the correct sign and non-zero position. The video decoder 300 determines the final MV by adding the MVD size and the determined sign to the previously determined MVP.

Accordingly, in light of the above, in one example of the present disclosure, video decoder 300 may determine the sign of the components of the MVD for the MMVD mode using the following techniques. Video decoder 300 may construct a motion vector candidate using the possible sign values, the respective magnitudes of the motion vector difference components, and a motion vector predictor for the block of video data. Possible sign values include positive and negative sign values for each of the possible components (x component and y component) of the MVD, for example as shown in Table 2 above.

In one example, video decoder 300 may decode a merge index representing a motion vector predictor from a merge candidate list. Video decoder 300 may determine the size of each of the motion vector difference components by decoding the step index above (e.g., distance IDX in Table 1) that represents the size of each of the motion vector difference components.

Video decoder 300 may be further configured to sort the motion vector candidates based on a cost for each of the motion vector candidates to generate an ordered list. Video decoder 300 can sort the list in ascending or descending cost order. As discussed above, video decoder 300 may use a SAD metric based on template matching to determine the cost for each of the candidates. Video decoder 300 can then determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the ordered list. For example, video decoder 300 may decode a motion vector sign predictor index from an encoded video bitstream. The motion vector sign predictor index indicates a specific motion vector candidate in the sorted candidate list. Video decoder 300 may determine the sign value for the MVD magnitude to use in determining the final motion vector from the sign value of the motion vector candidate in the sorted list that corresponds to the motion vector sign predictor index.

Video decoder 300 may then decode the block of video data using the respective magnitudes of the motion vector difference coordinates and the respective motion vector difference sign for each motion vector difference component. For example, video decoder 300 may determine the motion vector difference by applying each motion vector difference sign for each motion vector difference component to each magnitude of the motion vector difference component, and determine the motion vector difference by applying the motion vector difference sign for each motion vector difference component to the respective magnitude of the motion vector difference component. In addition to the predictor, we can determine the final motion vector and use the final motion vector to decode blocks of video data. In this way, the sign for the size of the MVD component can be determined with less signaling overhead, thereby increasing coding efficiency.

MMVD direction/sign prediction for affine MMVD

Similar to the MMVD sign/direction prediction procedure described above, the MMVD sign predictor index for affine MMVD can also be derived in a similar manner. However, there are some differences due to the nature of the affine inter prediction mode.

First, since the MVD for different CPMVs remains the same, the same MVD is added to each CPMV to derive the final CPMV.

Second, CPMV is not used directly to generate reference templates. For each 4x4 subblock, a motion vector field is generated based on the affine motion model.

Finally, templates for both the current block and the reference block are created based on the motion vector of each sub-block, and the template matching cost is aggregated for each sub-block to become the final template matching cost.

Once the template matching cost is derived, the MMVD direction predictor index is used again in the same way as in MMVD to derive the actual MVD.

MMVD sign/direction prediction for GPM MMVD

MMVD sign/direction prediction can also be extended to GPM MMVD. Due to the nature of GPM MMVD, some changes may be implemented compared to the MVD sign prediction design used in MMVD described above.

For bidirectional prediction, unlike MMVD and affine MMVD, where one MVD is the same, opposite, or scaled version of another MVD, in GPM MMVD mode there is no correlation between the two MVDs for the two GPM partitions. Due to this fact, it may be necessary to signal up to two MMVD sign predictor indices and the derivation of the MMVD sign predictor is performed separately for each GPM partition.

Additionally, due to the additional introduction of diagonal and anti-diagonal directions, the number of possible MVD code combinations increased from 4 to 8.

MVD sign prediction for MHP

MHP's final predictor includes the base and up to two additional hypotheses. For MHP, the base may be any one of inter mode, affine mode, merge mode, affine merge mode, inter MMVD mode, and affine MMVD mode. An additional hypothesis could be either one-way inter mode or one-way merge mode.

Therefore, MVD sign prediction is applicable to MHP in both MHP base and additive hypotheses. MVD sign prediction can be applied to the MHP base if the base is inter mode, affine mode, inter MMVD mode, or affine MMVD mode. If the additional hypothesis is selected as the inter prediction mode, MVD sign prediction can also be applied. MVD sign predictor indices for MHP base and hypothesis are generated separately.

MVD sign prediction can be applied to both the MHP base and hypothesis, but in some instances MVD sign prediction is allowed to be used only for the MHP base. In another example, MVD sign prediction applies only to the additive hypothesis.

Create MVD sign prediction template

In MVD sign prediction, the template can be selected differently. First, the template shape can have various variations. For example, both the top template and the left template are used, and the template is L-shaped. In another example, only the top template is used. In the third example, only the left template is used.

Second, templates can be created using different interpolation filters. In template matching (TM) merge mode, templates are created using a bilinear interpolation filter. For templates in MVD sign prediction, the same bilinear filter can be used to generate the template. In another example, a template can be created using a 12-tap interpolation filter.

Third, you can choose different template sizes. Generally, the template size for inter mode is selected as 4 rows and 4 columns; The template size in affine mode is selected as 1 row and 1 column. However, the template size can be changed. For example, the template size of affine mode can be increased to the same as that of inter mode. In another example, the template may be subsampled by a given factor to reduce computational complexity.

MVD sign prediction cost derivation

In addition to the template matching cost, other costs may also be used in MVD code prediction. In one example, instead of using a template, a reconstructed block can be created by adding a reconstructed residual signal, which can be signaled in the form of a quantized transform coefficient, to the predictor. Thereafter, video decoder 300 may derive the cost between the currently reconstructed block and the reference block. In another example, the cost of MVD sign prediction can be derived using the gradient value around the current block boundary.

A variety of norms can be used when deriving costs. In general, the L1 norm, SAD (Sum of Absolute Difference), or the L2 norm, SSD (Sum of Square Error), can be used. However, in principle, other Ln norms and other known norms can be used.

Bidirectional prediction can be selected for translational inter SMVD (symmetric MVD) mode, inter MMVD, and affine MMVD mode. Also, only the MVD for one reference list needs to be signaled and the MVD for the other lists can be derived from the first list. In this case, when deriving the MVD sign prediction cost, reference blocks/templates from a single list or reference blocks/templates from both reference lists can be used in the MVD sign prediction process.

In one example, only reference blocks/templates in reference list 0 are used to derive the cost. In the second example, only the reference block/template in reference list 1 is used to derive the cost. In the third example, the cost is derived using reference blocks/templates from both reference list 0 and list 1. In another example, one reference list may derive a template matching cost based on the current block's template and a reference template, and a second part of the cost is derived from the two-way matching cost between reference list 0 and the reference block in list 1. .

MVD sign prediction threshold

MVD sign prediction can be conditionally applied to specific blocks when certain thresholds are met. To make MVD sign prediction stable, it may be advantageous for the block size to be large enough to contain an appropriate number of samples for cost derivation. Moreover, the MVD size is preferably large enough so that all possible final MVs can be distributed sparsely to include different image regions in the cost derivation. Therefore, in one example, a block size based threshold (usually defined by the number of samples within the block) is applied and only blocks with a block size greater than (or equal to) the threshold can use MVD sign prediction. In another example, the MVD size threshold is used to determine whether MVD sign prediction can be applied to a block. In another example, a combination of two thresholds may be applied.

Alternatively, a separate context may be applied to the context-coded MVD code bin or MMVD direction prediction index depending on the MVD size. This assumes that the MVD size is known before parsing the MVD sign bin or MMVD direction prediction index.

common example

The MVD sign prediction process can be described as follows:

One. Parsing the size of MVD components.

2. Parsing context-coded MVD sign predictor indices.

3. Build MV candidates by generating combinations between possible signs and absolute MVD values and add them to the MV predictor.

4. Derive the MVD sign prediction cost for each derived MV based on some metrics and alignment.

5. Select the actual MVD sign using the corresponding MVD sign predictor index.

6. Adding the actual MVD to the MV predictor for the final MV.

All examples mentioned in the above section can be applied to all inter prediction modes where MVD sign prediction is applicable. These modes include inter MMVD, affine MMVD, GPM MMVD, and MHP, the modes detailed in this document. MVD sign prediction can also be applied to translational inter mode, SMVD mode, and affine inter mode.

Accordingly, in one example of the present disclosure, video decoder 300 decodes the magnitude of the motion vector difference coordinates for a block of video data, decodes the motion vector sign predictor index, possible sign values, and the magnitude of the motion vector difference coordinates. , construct motion vector candidates, derive the motion vector difference sign prediction cost for each motion vector candidate, sort the motion vector candidates based on the cost for each motion vector candidate to generate a sorted list, and The vector difference sign is determined based on the motion vector sign predictor index and the sorted list, and the block of video data is decoded using the size of the motion vector difference coordinate and the motion vector difference sign.

FIG. 8 is a block diagram illustrating an example video encoder 200 that may perform the techniques of this disclosure. 8 is provided for illustrative purposes and should not be considered limiting of the techniques as broadly illustrated and described in this disclosure. For purposes of explanation, this disclosure describes a video encoder 200 according to the techniques of VVC (ITU-T H.266, under development) and HEVC (ITU-T H.265). However, the techniques of this disclosure may be performed by video encoding devices configured with other video coding standards and video coding formats, such as AV1 and successors to the AV1 video coding format.

In the example of Figure 8, video encoder 200 includes video data memory 230, mode selection unit 202, residual generation unit 204, transform processing unit 206, quantization unit 208, and inverse quantization unit ( 210), inverse transform processing unit 212, reconstruction unit 214, filter unit 216, decoded picture buffer (DPB) 218, and entropy encoding unit 220. Video data memory 230, mode selection unit 202, residual generation unit 204, transform processing unit 206, quantization unit 208, inverse quantization unit 210, inverse transform processing unit 212, reconstruction Any or all of unit 214, filter unit 216, DPB 218, and entropy encoding unit 220 may be implemented in one or more processors or in processing circuitry. For example, a unit of video encoder 200 may be implemented as one or more circuits or logic elements, as part of a hardware circuit or as part of a processor, ASIC, or FPGA. Moreover, video encoder 200 may include additional or alternative processors or processing circuitry to perform these and other functions.

Video data memory 230 may store video data to be encoded by components of video encoder 200.　 Video encoder 200 may receive video data stored in video data memory 230, for example, from video source 104 (Figure 1). 　 DPB 218 may act as a reference picture memory to store reference video data for use in prediction of subsequent video data by video encoder 200.　 Video data memory 230 and DPB 218 may be dynamic random access memory (DRAM), including synchronous dynamic random access memory (SDRAM), magnetoresistive RAM (MRAM), resistive RAM (RRAM), or other types of memory devices. It may be formed by any of a variety of memory devices such as:　 Video data memory 230 and DPB 218 may be provided by the same memory device or separate memory devices. 　In various examples, video data memory 230 may be on-chip with other components of video encoder 200, as illustrated, or off-chip relative to those components.

In this disclosure, references to video data memory 230 should not be construed as limited to memory internal to video encoder 200 unless specifically stated as such, or memory external to video encoder 200 unless specifically stated as such. do. Rather, references to video data memory 230 should be understood as a reference memory that stores video data that video encoder 200 receives for encoding (e.g., video data for the current block to be encoded). Memory 106 of FIG. 1 may also provide temporary storage of outputs from various units of video encoder 200.

The various units in FIG. 8 are illustrated to aid understanding of the operations performed by video encoder 200. Units may be implemented as fixed function circuits, programmable circuits, or a combination thereof. Fixed function circuits refer to circuits that provide specific functionality and are preset for the operations that can be performed. Programmable circuits refer to circuits that can be programmed to perform various tasks, providing flexible functionality in the operations that can be performed. For example, programmable circuits may execute software or firmware that causes the programmable circuits to operate in a manner defined by instructions of the software or firmware. Fixed function circuits may execute software instructions (eg, to receive parameters or output parameters), but the types of operations that fixed function circuits perform are generally immutable. In some examples, one or more of the units may be individual circuit blocks (fixed function or programmable), and in some examples, one or more of the units may be integrated circuits.

Video encoder 200 is formed from programmable circuits, such as arithmetic logic units (ALUs), elementary function units (EFUs), digital circuits, analog circuits, and/or programmable circuits. It may also include cores. In instances where the operations of video encoder 200 are performed using programmable circuits, software executed by memory 106, memory 106 (FIG. 1) may be configured to store the software that video encoder 200 receives and executes. of instructions (e.g., object code), or other memory within video encoder 200 (not shown) may store such instructions.

Video data memory 230 is configured to store received video data. Video encoder 200 may retrieve a picture of video data from video data memory 230 and provide the video data to residual generation unit 204 and mode select unit 202. Video data in video data memory 230 may be raw video data to be encoded.

Mode selection unit 202 includes motion estimation unit 222, motion compensation unit 224, and intra-prediction unit 226. Mode selection unit 202 may include additional functional units to perform video prediction according to different prediction modes. For example, mode selection unit 202 may be a palette unit, an intra-block copy unit (which may be part of motion estimation unit 222 and/or motion compensation unit 224), an affine unit, a linear model (LM) unit. etc. may also be included.

Mode select unit 202 generally coordinates multiple encoding passes to test combinations of encoding parameters and the resulting rate-distortion values for those combinations. Encoding parameters may include partitioning of CTUs into CUs, prediction modes for CUs, transformation types for residual data of CUs, quantization parameters for residual data of CUs, etc. Mode select unit 202 may ultimately select a combination of encoding parameters that has better rate-distortion values than other tested combinations.

Video encoder 200 may partition a picture retrieved from video data memory 230 into a series of CTUs and encapsulate one or more CTUs within a slice. Mode select unit 202 may partition the CTUs of the picture according to a tree structure, such as an MTT structure, QTBT structure, superblock structure, or quadtree structure described above. As described above, video encoder 200 may form one or more CUs from partitioning a CTU according to a tree structure. Such CUs may also be generally referred to as “video blocks” or “blocks.”

In general, mode select unit 202 also controls its components (e.g., motion estimation unit 222, motion compensation unit 224, and intra-prediction unit 226) to select the current block (e.g. For example, generate a prediction block for the current CU (or, in HEVC, the overlapping portion of PU and TU). For inter-prediction of the current block, motion estimation unit 222 selects one or more closely matching reference blocks from one or more reference pictures (e.g., one or more previously coded pictures stored in DPB 218). A motion search may also be performed to identify them. In particular, motion estimation unit 222 may determine potential reference blocks according to, for example, sum of absolute differences (SAD), sum of squared differences (SSD), mean absolute difference (MAD), mean squared differences (MSD), etc. We can also calculate a value indicating how similar this block is to the current block. Motion estimation unit 222 may perform these calculations using sample-by-sample differences between a generally considered reference block and the current block. Motion estimation unit 222 may identify the reference block with the lowest value resulting from these calculations, which indicates the reference block that most closely matches the current block.

Motion estimation unit 222 may form one or more motion vectors (MVs) that define positions of reference blocks in reference pictures relative to the position of the current block in the current picture. Motion estimation unit 222 may then provide motion vectors to motion compensation unit 224. For example, for unidirectional inter-prediction, motion estimation unit 222 may provide a single motion vector, while for bidirectional inter-prediction, motion estimation unit 222 may provide two motion vectors. there is. Motion compensation unit 224 may then use the motion vectors to generate a prediction block. For example, motion compensation unit 224 may use the motion vector to retrieve data of a reference block. As another example, if the motion vector has fractional sample precision, motion compensation unit 224 may interpolate the values for the prediction block according to one or more interpolation filters. Additionally, for bi-directional inter-prediction, motion compensation unit 224 retrieves data for two reference blocks identified by their respective motion vectors, e.g., through sample-by-sample averaging or weighted averaging. Data can also be combined.

When operating according to the AV1 video coding format, motion estimation unit 222 and motion compensation unit 224 may perform translational motion compensation, affine motion compensation, overlapped block motion compensation (OBMC), and/or complex inter-intra prediction. may be configured to encode coding blocks (e.g., both luma and chroma coding blocks) of video data.

As another example, for intra-prediction, or intra-predictive coding, intra-prediction unit 226 may generate a prediction block from samples neighboring the current block. For example, for directional modes, intra-prediction unit 226 may typically generate a prediction block by mathematically combining the values of neighboring samples and populating these calculated values in a defined direction across the current block. It may be possible. As another example, for DC mode, intra-prediction unit 226 may calculate the average of neighboring samples for the current block and generate a prediction block to include the average of these results for each sample of the prediction block. there is.

When operating according to the AV1 video coding format, intra prediction unit 226 may perform directional intra prediction, non-directional intra prediction, recursive filter intra prediction, chroma-from-luma (CFL) prediction, intra block copy (IBC), and/or encode coding blocks (e.g., both luma and chroma coding blocks) of video data using a color palette mode. Mode selection unit 202 may include additional functional units to perform video prediction according to different prediction modes.

Mode selection unit 202 provides the prediction block to residual generation unit 204. Residual generation unit 204 receives a raw, uncoded version of the current block from video data memory 230 and a prediction block from mode select unit 202. The residual generation unit 204 calculates the sample-by-sample difference between the current block and the prediction block. The sample-by-sample differences in the results define the residual block for the current block. In some examples, residual generation unit 204 may also determine differences between sample values in a residual block to generate the residual block using residual differential pulse code modulation (RDPCM). In some examples, residual generation unit 204 may be formed using one or more subtraction circuits that perform binary subtraction.

In examples where mode select unit 202 partitions CUs into PUs, each PU may be associated with a luma prediction unit and corresponding chroma prediction units. Video encoder 200 and video decoder 300 may support PUs of various sizes. As indicated above, the size of a CU may refer to the size of a luma coding block of the CU and the size of a PU may refer to the size of a luma prediction unit of the PU. Assuming that the size of a specific CU is 2Nx2N, video encoder 200 supports PU sizes of 2Nx2N or NxN for intra-prediction, and symmetric PU sizes of 2Nx2N, 2NxN, Nx2N, NxN, etc. for inter-prediction. Sizes may also be supported. Video encoder 200 and video decoder 300 may also support asymmetric partitioning for PU sizes of 2NxnU, 2NxnD, nLx2N, and nRx2N for inter-prediction.

In examples where mode select unit 202 does not further partition the CU into PUs, each CU may be associated with a luma coding block and corresponding chroma coding blocks. As above, the size of a CU may refer to the size of the luma coding block of the CU. Video encoder 200 and video decoder 300 may support CU sizes of 2Nx2N, 2NxN, or Nx2N.

As some examples, for other video coding techniques such as intra-block copy mode coding, affine-mode coding, and linear model (LM) mode coding, mode selection unit 202 selects individual units associated with the coding techniques. Through this, a prediction block for the current block being encoded is generated. In some examples, such as palette mode coding, mode select unit 202 may not generate a predictive block, but instead generate syntax elements indicating how to reconstruct the block based on the selected palette. In such modes, mode select unit 202 may provide these syntax elements to entropy encoding unit 220 to be encoded.

As described above, residual generation unit 204 receives video data for the current block and the corresponding prediction block. Residual generation unit 204 then generates a residual block for the current block. To generate a residual block, residual generation unit 204 calculates sample-by-sample differences between the current block and the prediction block.

Transform processing unit 206 applies one or more transforms to the residual block to generate a block of transform coefficients (referred to herein as a “transform coefficient block”). Transform processing unit 206 may apply various transforms to the residual block to form a transform coefficient block. For example, transform processing unit 206 may apply a discrete cosine transform (DCT), a directional transform, a Karhunen-Loeve transform (KLT), or a conceptually similar transform to the residual block. In some examples, transform processing unit 206 may perform multiple transforms on the residual block, such as a first-order transform and a second-order transform, such as a rotation transform. In some examples, transform processing unit 206 does not apply transforms to the residual block.

When operating in accordance with AV1, transform processing unit 206 may apply one or more transforms to the residual block to generate a block of transform coefficients (referred to herein as a “transform coefficient block”). Transform processing unit 206 may apply various transforms to the residual block to form a transform coefficient block. For example, transform processing unit 206 may include a discrete cosine transform (DCT), an asymmetric discrete sine transform (ADST), an inverted ADST (e.g., inverse ADST), and an identity transform (IDTX). /vertical transformation combination can be applied. When using an identity transformation, the transformation is skipped in either the vertical or horizontal direction. In some examples, you may want to skip the conversion process.

Quantization unit 208 may quantize the transform coefficients in a transform coefficient block to generate a quantized transform coefficient block. Quantization unit 208 may quantize the transform coefficients of the transform coefficient block according to a quantization parameter (QP) value associated with the current block. Video encoder 200 may adjust the degree of quantization applied to transform coefficient blocks associated with the current block by adjusting the QP value associated with the CU (e.g., via mode select unit 202). Quantization may introduce loss of information, and thus quantized transform coefficients may have lower precision than the original transform coefficients generated by transform processing unit 206.

Inverse quantization unit 210 and inverse transform processing unit 212 may apply inverse quantization and inverse transforms, respectively, to the quantized transform coefficient block to reconstruct a residual block from the transform coefficient block. Reconstruction unit 214 may generate a reconstructed block corresponding to the current block (potentially with some degree of distortion) based on the prediction block and the reconstructed residual block generated by mode selection unit 202. It may be possible. For example, reconstruction unit 214 may add samples of the reconstructed residual block to corresponding samples from the prediction block generated by mode select unit 202 to produce a reconstructed block.

Filter unit 216 may perform one or more filter operations on the reconstructed block. For example, filter unit 216 may perform deblocking operations to reduce blockiness artifacts along the edges of CUs. Operations of filter unit 216 may be skipped in some examples.

When operating in accordance with AV1, filter unit 216 may perform one or more filter operations on the reconstructed blocks. For example, filter unit 216 may perform deblocking operations to reduce blockiness artifacts along the edges of CUs. In other examples, filter unit 216 may apply a constrained directional enhancement filter (CDEF), which may be applied after deblocking and a series of non-separable nonlinear low-pass directional filters based on the estimated edge directions. May also include application. Filter unit 216 may also include a loop restoration filter applied after CDEF, a separable symmetric normalized Wiener filter or a dual self-guided filter.

Video encoder 200 stores the reconstructed blocks in DPB 218. For example, in instances where the operations of filter unit 216 are not performed, reconstruction unit 214 may store the reconstructed blocks in DPB 218. In examples in which the operations of filter unit 216 are performed, filter unit 216 may store the filtered reconstructed blocks in DPB 218. Motion estimation unit 222 and motion compensation unit 224 may retrieve a reference picture from DPB 218 formed from the reconstructed (and potentially filtered) blocks to inter-predict blocks of subsequently encoded pictures. there is. Additionally, intra-prediction unit 226 may use the reconstructed blocks in DPB 218 of the current picture to intra-predict other blocks in the current picture.

In general, entropy encoding unit 220 may entropy encode syntax elements received from other functional components of video encoder 200. For example, entropy encoding unit 220 may entropy encode quantized transform coefficient blocks from quantization unit 208. As another example, entropy encoding unit 220 may entropy encode prediction syntax elements (e.g., intra-mode information for intra-prediction or motion information for inter-prediction) from mode selection unit 202. there is. Entropy encoding unit 220 may perform one or more entropy encoding operations on syntax elements, another example of video data, to generate entropy-encoded data. For example, entropy encoding unit 220 may support context-adaptive variable length coding (CAVLC) operations, CABAC operations, variable-to-variable (V2V) length coding operations, and syntax-based context-adaptive binary arithmetic coding (SBAC) operations. A probability interval partitioning entropy (PIPE) coding operation, an exponential-Golomb encoding operation, or another type of entropy encoding operation may be performed on the data. In some examples, entropy encoding unit 220 may operate in a bypass mode in which syntax elements are not entropy encoded.

Video encoder 200 may output a bitstream containing entropy encoded syntax elements needed to reconstruct blocks of a picture or slice. In particular, entropy encoding unit 220 may output a bitstream.

According to AV1, entropy encoding unit 220 may be configured as a symbol-to-symbol adaptive multi-symbol arithmetic coder. A syntax element in AV1 contains an alphabet of N elements, and the context (eg, a probability model) contains a set of N probabilities. Entropy encoding unit 220 may store probabilities as n-bit (e.g., 15-bit) cumulative distribution functions (CDFs). Entropy encoding unit 220 may perform recursive scaling with an update factor based on the alphabet size to update the context.

The operations described above are described in terms of blocks. Such description should be understood as operations on luma coding blocks and/or chroma coding blocks. As described above, in some examples, the luma coding block and chroma coding blocks are the luma and chroma components of a CU. In some examples, the luma coding block and chroma coding blocks are luma and chroma components of a PU.

In some examples, operations performed on a luma coding block do not need to be repeated for chroma coding blocks. As one example, the operations of identifying the motion vector (MV) and reference picture for a luma coding block do not need to be repeated to identify the motion vector (MV) and reference picture for the chroma blocks. Rather, the MV for the luma coding block may be scaled to determine the MV for the chroma blocks, and the reference picture may be the same. As another example, the intra-prediction process may be the same for luma coding blocks and chroma coding blocks.

Video encoder 200 is a device configured to encode video data, including a memory configured to store video data, and one or more processing units implemented in circuitry and configured to perform one or more example techniques described in this disclosure. Shows an example.

9 is a block diagram illustrating an example video decoder 300 that may perform the techniques of this disclosure. 9 is provided for illustrative purposes and is not limiting to the techniques broadly exemplified and described in this disclosure. For purposes of explanation, this disclosure describes a video decoder 300 according to the techniques of VVC (ITU-T H.266, under development) and HEVC (ITU-T H.265). However, the techniques of this disclosure may be performed by video coding devices configured with other video coding standards.

In the example of FIG. 9 , video decoder 300 includes coded picture buffer (CPB) memory 320, entropy decoding unit 302, prediction processing unit 304, inverse quantization unit 306, and inverse transform processing unit. 308, restoration unit 310, filter unit 312, and decoded picture buffer (DPB) 314. CPB memory 320, entropy decoding unit 302, prediction processing unit 304, inverse quantization unit 306, inverse transform processing unit 308, restoration unit 310, filter unit 312, and DPB ( Any or all of 314) may be implemented in one or more processors or processing circuitry. For example, units of video decoder 300 may be implemented as one or more circuits or logic elements as part of hardware circuitry, a processor in an FPGA, an ASIC. Moreover, video decoder 300 may include additional or alternative processors or processing circuitry to perform these and other functions.

Prediction processing unit 304 includes motion compensation unit 316 and intra-prediction unit 318. Prediction processing unit 304 may include additional units to perform prediction according to different prediction modes. As examples, prediction processing unit 304 may include a palette unit, an intra-block copy unit (which may form part of motion compensation unit 316), an affine unit, a linear model (LM) unit, etc. In other examples, video decoder 300 may include more, fewer, or different functional components.

When operating according to AV1, compensation unit 316 may use translational motion compensation, affine motion compensation, OBMC, and/or complex inter-intra prediction, as described above, to code blocks of video data (e.g., luma and can be configured to decode both chroma coding blocks). Intra prediction unit 318 uses directed intra prediction, non-directional intra prediction, recursive filter intra prediction, CFL, intra block copy (IBC), and/or color palette modes as described above to code blocks of video data (e.g. For example, both luma and chroma coding blocks).

CPB memory 320 may store video data, such as an encoded video bitstream, to be decoded by components of video decoder 300.　 Video data stored in CPB memory 320 may be obtained, for example, from computer-readable medium 110 (FIG. 1). 　 CPB memory 320 may include a CPB that stores encoded video data (e.g., syntax elements) from an encoded video bitstream.　 Additionally, CPB memory 320 may store video data other than syntax elements of a coded picture, such as temporal data representing outputs from various units of video decoder 300. DPB 314 generally stores decoded pictures that video decoder 300 may output and/or use as reference video data when decoding subsequent data or pictures of the encoded video bitstream.　 CPB memory 320 and DPB 314 may be formed by any of a variety of memory devices, such as DRAM, including SDRAM, MRAM, RRAM, or other types of memory devices.　 CPB memory 320 and DPB 314 may be provided by the same memory device or separate memory devices. In various examples, CPB memory 320 may be on-chip with other components of video decoder 300, or off-chip relative to those components.

Additionally or alternatively, in some examples, video decoder 300 may retrieve coded video data from memory 120 (Figure 1). That is, memory 120 may store data as discussed above with CPB memory 320. Likewise, memory 120 may store instructions to be executed by video decoder 300 when some or all of the functionality of video decoder 300 is implemented in software that is executed by the processing circuitry of video decoder 300. .

The various units shown in FIG. 9 are illustrated to aid understanding of the operations performed by video decoder 300. These units may be implemented as fixed function circuits, programmable circuits, or a combination thereof. Similar to Figure 3, similar to Figure 8, fixed function circuits refer to circuits that provide specific functionality and are preset for the operations that can be performed. Programmable circuits refer to circuits that can be programmed to perform various tasks, providing flexible functionality in the operations that can be performed. For example, programmable circuits may execute software or firmware that causes the programmable circuits to operate in a manner defined by instructions of the software or firmware. Fixed function circuits may execute software instructions (eg, to receive parameters or output parameters), but the types of operations that fixed function circuits perform are generally immutable. In some examples, one or more of the units may be individual circuit blocks (fixed function or programmable), and in some examples, one or more of the units may be integrated circuits.

Video decoder 300 may include ALUs, EFUs, digital circuits, analog circuits, and/or programmable cores formed from programmable circuits. In examples where the operations of video decoder 300 are performed by software executing on programmable circuits, on-chip or off-chip memory may store instructions of the software that video decoder 300 receives and executes (e.g. , object code) can also be saved.

Entropy decoding unit 302 may receive encoded video data from CPB and entropy decode the video data to reproduce syntax elements. Prediction processing unit 304, inverse quantization unit 306, inverse transform processing unit 308, restoration unit 310, and filter unit 312 decode video data based on syntax elements extracted from the bitstream. You can also create .

In general, video decoder 300 reconstructs a picture on a block-by-block basis. Video decoder 300 may perform a reconstruction operation on each block individually (where the block currently being reconstructed, i.e., being decoded, may be referred to as the “current block”).

Entropy decoding unit 302 may entropy decode syntax elements defining quantized transform coefficients of a quantized transform coefficient block, as well as transform information, such as quantization parameter (QP) and/or transform mode indication(s). Inverse quantization unit 306 may use the QP associated with the quantized transform coefficient block to determine the degree of quantization and, similarly, the degree of inverse quantization that inverse quantization unit 306 will apply. Inverse quantization unit 306 may perform a bitwise left-shift operation, for example, to inverse quantize quantized transform coefficients. Accordingly, inverse quantization unit 306 may form a transform coefficient block containing transform coefficients.

After inverse quantization unit 306 forms the transform coefficient block, inverse transform processing unit 308 may apply one or more inverse transforms to the transform coefficient block to generate a residual block associated with the current block. For example, inverse transform processing unit 308 may apply an inverse DCT, an inverse integer transform, an inverse Karhunen-Loeve transform (KLT), an inverse rotation transform, an inverse directional transform, or another inverse transform to the transform coefficient block.

Prediction processing unit 304 also generates a prediction block according to prediction information syntax elements entropy decoded by entropy decoding unit 302. For example, if prediction information syntax elements indicate that the current block is inter-predicted, motion compensation unit 316 may generate a prediction block. In this case, the prediction information syntax elements may indicate a motion vector that identifies the location of the reference block in the reference picture relative to the location of the current block in the current picture, as well as the reference picture in DPB 314 from which to retrieve the reference block. It may be possible. Motion compensation unit 316 may perform the inter-prediction process generally in a manner substantially similar to that described for motion compensation unit 224 (Figure 8).

As another example, if the prediction information syntax elements indicate that the current block is intra-prediction, intra-prediction unit 318 may generate the prediction block according to the intra-prediction mode indicated by the prediction information syntax elements. Again, intra-prediction unit 318 may perform the intra-prediction process generally in a manner substantially similar to that described for intra-prediction unit 226 (Figure 8). Intra-prediction unit 318 may retrieve data of neighboring samples for the current block from DPB 314.

Reconstruction unit 310 may reconstruct the current block using the prediction block and the residual block. For example, reconstruction unit 310 may add samples of the residual block to corresponding samples of the prediction block to reconstruct the current block.

Filter unit 312 may perform one or more filter operations on the reconstructed blocks. For example, filter unit 312 may perform deblocking operations to reduce blockiness artifacts along the edges of reconstructed blocks. The operations of filter unit 312 are not necessarily performed in all examples.

Video decoder 300 may store the reconstructed blocks in DPB 314. For example, in instances where the operations of filter unit 312 are not performed, reconstruction unit 310 may store the reconstructed blocks in DPB 314. In examples in which the operations of filter unit 312 are performed, filter unit 312 may store the filtered reconstructed blocks in DPB 314. As described above, DPB 314 may provide prediction processing unit 304 with reference information, such as samples of the current picture for intra-prediction and previously decoded pictures for subsequent motion compensation. Moreover, video decoder 300 may output decoded pictures (e.g., decoded video) from DPB 314 for subsequent presentation on a display device, such as display device 118 of FIG. 1.

In this manner, video decoder 300 represents an example of a video decoding device, the video decoder comprising a memory configured to store video data, and one or more processing units implemented in circuitry, wherein the one or more processing units are configured to store possible sign values. , the respective magnitudes of the motion vector difference components, and constructing motion vector candidates using a motion vector predictor for a block of video data, wherein possible sign values include positive sign values and negative sign values. Construct motion vector candidates; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

10 is a flowchart illustrating an example method for encoding a current block in accordance with the techniques of this disclosure. The current block may include the current CU. Although described with respect to video encoder 200 ( FIGS. 1 and 8 ), it should be understood that other devices may be configured to perform methods similar to those of FIG. 10 .

In this example, video encoder 200 initially predicts the current block (350). For example, video encoder 200 may form a prediction block for the current block. Video encoder 200 may then calculate a residual block for the current block (352). To calculate the residual block, video encoder 200 may calculate the difference between the original, unencoded block and the prediction block for the current block. Video encoder 200 may then transform the residual block and quantize the transform coefficients of the residual block (354). Next, video encoder 200 may scan the quantized transform coefficients of the residual block (356). During, or following the scan, video encoder 200 may entropy encode the transform coefficients (358). For example, video encoder 200 may encode transform coefficients using CAVLC or CABAC. Video encoder 200 may then output the block's entropy encoded data (360).

11 is a flow chart illustrating an example method for decoding a current block of video data in accordance with the techniques of this disclosure. The current block may include the current CU. Although described with respect to video encoder 200 ( FIGS. 1 and 9 ), it should be understood that other devices may be configured to perform methods similar to those of FIG. 11 .

Video decoder 300 may receive entropy encoded data for a current block, such as entropy encoded prediction information and entropy encoded data for transform coefficients of a residual block corresponding to the current block (370). Video decoder 300 may entropy decode the entropy encoded data to determine prediction information for the current block and reproduce the transform coefficients of the residual block (372). Video decoder 300 may predict the current block, e.g., using an intra- or inter-prediction mode, as indicated by the prediction information for the current block, to calculate a prediction block for the current block (374 ). Video decoder 300 may then reverse scan the reproduced transform coefficients to generate a block of quantized transform coefficients (376). Video decoder 300 may then inverse quantize the transform coefficients and apply an inverse transform to the transform coefficients to generate a residual block (378). Video decoder 300 may ultimately decode the current block by combining the prediction block and the residual block (380).

12 is a flow chart illustrating another example method for decoding a current block in accordance with the techniques of this disclosure. The techniques of FIG. The techniques of FIG. 12 may be performed by one or more structural components of video decoder 300, including motion compensation unit 316.

In one example of the present disclosure, video decoder 300 constructs motion vector candidates using the possible sign values, respective magnitudes of the motion vector difference components, and a motion vector predictor for a block of video data, Possible sign values may be configured to configure the motion vector candidates, including positive sign values and negative sign values (1200). Video decoder 300 may be further configured to sort the motion vector candidates based on a cost for each of the motion vector candidates to generate an ordered list (1202). Video decoder 300 may further determine 1204 each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the ordered list, and each motion vector difference sign for each motion vector difference component. A block of video data may be decoded using the respective sizes of the motion vector difference sign and the motion vector difference coordinate (1206).

In the example above, a block of video data may be coded using one of the following: Merge with Intermotion Vector Differences (MMVD) mode, affine MMVD, Geometric Partitioning Mode with MMVD (GPM), or Multiple Hypothesis Prediction (MHP) mode. .

In a specific example, a block of video data is coded using inter MMVD mode. In this example, video decoder 300 may be further configured to decode a merge index representing a motion vector predictor, decode a step index representing the respective magnitude of the motion vector difference coordinate, and decode a motion vector sign predictor index. there is. The video decoder 300 determines the motion vector difference by applying each motion vector difference sign for each motion vector difference component to each size of the motion vector difference component, and adds the motion vector difference to the motion vector predictor to obtain a final The method may be further configured to determine a motion vector and decode a block of video data using the resulting motion vector.

In another specific example, a block of video data is coded using an affine MMVD mode and the motion vector predictor includes two or three control point motion vectors. In this example, video decoder 300 may be further configured to determine control point motion vectors, decode a step index indicating the respective magnitude of the motion vector difference coordinate, and decode a motion vector sign predictor index. The video decoder 300 determines the motion vector difference by applying each motion vector difference sign for each motion vector difference component to each size of the motion vector difference component, and applies the motion vector difference to each of the control point motion vectors. The method may further be configured to determine a final control point motion vector and decode a block of video data using the final control point motion vector.

In any of the above examples, video decoder 300 may be further configured to determine cost using template matching. As an example, when a block of video data is coded using an affine MMVD merge with motion vector difference (MMVD) mode, video decoder 300 may be configured to determine the cost using subblock-based template matching. Moreover, in any of the above examples, video decoder 300 may be further configured to scale the magnitude of each of the motion vector difference components based on the picture order count (POC) difference.

Additional aspects of the disclosure are described below.

Aspect 1A - A method of coding video data, the method comprising: decoding magnitudes of motion vector difference coordinates for blocks of video data; decoding the motion vector sign predictor index; building a motion vector candidate using the possible sign values and magnitudes of the motion vector difference coordinates; deriving a motion vector difference sign prediction cost for each motion vector candidate; Sorting the motion vector candidates based on the cost for each motion vector candidate to generate a sorted list; determining a motion vector difference sign based on the motion vector sign predictor index and the sorted list; and decoding the block of video data using the magnitude of the motion vector difference coordinate and the motion vector difference sign.

Aspect 2A - The method of aspect 1A, wherein the block of video data is processed using one of the following: Merge with Intermotion Vector Differences (MMVD) mode, affine MMVD, Geometric Partitioning Mode with MMVD (GPM), and Multiple Hypothesis Prediction (MHP) mode. It is coded.

Aspect 3A - A device for coding video data, the device comprising one or more means for performing the method of any one of aspects 1A to 2A.

Aspect 4A - The device of aspect 3A, wherein the one or more means comprises one or more processors implemented in circuitry.

Aspect 5A - The device of aspect 3A or 4A, further comprising a memory for storing video data.

Aspect 6A - The device of any of aspects 3A-5A, further comprising a display configured to display decoded video data.

Aspect 7A - The device of any of aspects 3A-6A, wherein the device comprises one or more of a camera, a computer, a mobile device, a broadcast receiver device, or a set top box.

Aspect 8A - The device of any of aspects 3A-7A, wherein the device comprises a video decoder.

Aspect 9A - The device of any of aspects 3A-8A, wherein the device comprises a video encoder.

Aspect 10A - A computer-readable storage medium having instructions stored thereon that, when executed, cause one or more processors to perform the method of any of Aspects 1A-2A.

Aspect 11A - A device for coding video data, the device comprising: means for decoding magnitudes of motion vector difference coordinates for blocks of video data; means for decoding the motion vector sign predictor index; means for building a motion vector candidate using the possible sign values and magnitudes of the motion vector difference coordinates; means for deriving a motion vector difference sign prediction cost for each motion vector candidate; means for sorting the motion vector candidates based on a cost for each motion vector candidate to generate an ordered list; means for determining a motion vector difference sign based on the motion vector sign predictor index and the ordered list; and means for decoding the block of video data using the magnitude of the motion vector difference coordinate and the motion vector difference sign.

Aspect 1B - A method of decoding video data, the method comprising constructing motion vector candidates using possible sign values, respective magnitudes of motion vector difference components, and a motion vector predictor for a block of video data, comprising: Constructing the motion vector candidates, wherein possible sign values include positive sign values and negative sign values; Sorting the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determining each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decoding the block of video data using the respective magnitudes of the motion vector difference coordinates and the respective motion vector difference sign for each motion vector difference component.

Aspect 2B - The method of aspect 1B, wherein the block of video data is processed using one of a merge with inter motion vector difference (MMVD) mode, an affine MMVD, a geometric partitioning mode with MMVD (GPM), or a multiple hypothesis prediction (MHP) mode. It is coded.

Aspect 3B - In aspect 2B, a block of video data is decoded using an inter MMVD mode, the method comprising: decoding a merge index representing a motion vector predictor; decoding step indices representing respective magnitudes of motion vector difference coordinates; and decoding the motion vector sign predictor index.

Aspect 4B - The method of aspect 3B, comprising: determining a motion vector difference by applying each motion vector difference sign for each motion vector difference component to each magnitude of the motion vector difference component; adding the motion vector difference to a motion vector predictor to determine a final motion vector; It further includes decoding the block of video data using the final motion vector.

Aspect 5B - In aspect 2B, the block of video data is coded using an affine MMVD mode, the motion vector predictor includes two or three control point motion vectors, and the method includes determining the control point motion vector; decoding step indices representing respective magnitudes of motion vector difference coordinates; and decoding the motion vector sign predictor index.

Aspect 6B - In aspect 5B, the method includes determining a motion vector difference by applying a respective motion vector difference sign for each motion vector difference component to a respective magnitude of the motion vector difference component; adding the motion vector difference to each of the control point motion vectors to determine a final control point motion vector; and decoding the block of video data using the final control point motion vector.

Aspect 7B - The method of Aspect 1B, further comprising determining a cost using template matching.

Aspect 8B - The method of aspect 7B, wherein the video data block is coded using an affine MMVD merge using a Merge with Motion Vector Difference (MMVD) mode, and wherein determining the cost using the template matching comprises using a subblock-based template. It involves determining the cost using matching.

Aspect 9B - The method of aspect 1B, further comprising scaling said respective magnitudes of motion vector difference components based on a picture order count (POC) difference.

Aspect 10B - The method of aspect 1B, further comprising displaying a picture containing a decoded block of video data.

Aspect 11B - An apparatus configured to decode video data, the apparatus comprising a memory configured to store a block of video data, and one or more processors in communication with the memory, wherein the one or more processors are configured to decode possible sign values, motion vector difference components. Constructing motion vector candidates using respective magnitudes and a motion vector predictor for a block of video data, wherein possible sign values include positive sign values and negative sign values; ; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

Aspect 12B - The method of aspect 11B, wherein the block of video data uses one of a merge with inter motion vector difference (MMVD) mode, an affine MMVD, a geometric partitioning mode with MMVD (GPM), or a multiple hypothesis prediction (MHP) mode. It is coded.

Aspect 13B - In aspect 12B, a block of video data is decoded using an inter MMVD mode, and the one or more processors further decode a merge index representing a motion vector predictor; decode step indices representing respective magnitudes of motion vector difference coordinates; and decode the motion vector sign predictor index.

Aspect 14B - The method of aspect 13B, wherein the one or more processors further comprise: applying a respective motion vector difference sign for each motion vector difference component to a respective magnitude of the motion vector difference component to determine the motion vector difference; Add the motion vector difference to the motion vector predictor to determine the final motion vector; and configured to decode a block of video data using the final motion vector.

Aspect 15B - In aspect 12B, the block of video data is coded using an affine MMVD mode, the motion vector predictor includes two or three control point motion vectors, and the one or more processors further: decide; decode step indices representing respective magnitudes of motion vector difference coordinates; and decode the motion vector sign predictor index.

Aspects 16B - In aspect 15B, the one or more processors further comprise: applying a respective motion vector difference sign for each motion vector difference component to a respective magnitude of the motion vector difference component to determine a motion vector difference; Add the motion vector difference to each of the control point motion vectors to determine a final control point motion vector; and decode the block of video data using the final control point motion vector.

Aspect 17B - The aspect 16B, wherein the one or more processors are further configured to: determine cost using template matching.

Aspect 18B - The method of aspect 17B, wherein the video data block is coded using an affine MMVD merge using a Merge with Motion Vector Difference (MMVD) mode, and the one or more processors are further configured to determine the cost using template matching. , is configured to determine the cost using subblock-based template matching.

Aspect 19B - The method of aspect 11B, wherein the one or more processors are further configured to scale the respective magnitudes of motion vector difference components based on a picture order count (POC) difference.

Aspect 20B - The apparatus of aspect 11B, further comprising a display configured to display a picture comprising a decoded block of video data.

Aspect 1C - A method of decoding video data, the method comprising constructing motion vector candidates using possible sign values, respective magnitudes of motion vector difference components, and a motion vector predictor for a block of video data, comprising: Constructing the motion vector candidates, wherein possible sign values include positive sign values and negative sign values; Sorting the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determining each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decoding the block of video data using the respective magnitudes of the motion vector difference coordinates and the respective motion vector difference sign for each motion vector difference component.

Aspect 2C - The method of Aspect 1C, wherein the block of video data is processed using one of the following: Merge with Intermotion Vector Differences (MMVD) mode, affine MMVD, Geometric Partitioning Mode with MMVD (GPM), or Multiple Hypothesis Prediction (MHP) mode. It is coded.

Aspect 3C - In aspect 2C, a block of video data is decoded using an inter MMVD mode, the method comprising: decoding a merge index representing a motion vector predictor; decoding step indices representing respective magnitudes of motion vector difference coordinates; and decoding the motion vector sign predictor index.

Aspect 4C - The method of Aspect 3C, comprising: determining a motion vector difference by applying each motion vector difference sign for each motion vector difference component to each magnitude of the motion vector difference component; adding the motion vector difference to a motion vector predictor to determine a final motion vector; It further includes decoding the block of video data using the final motion vector.

Aspect 5C - In aspect 2C, the block of video data is coded using an affine MMVD mode, the motion vector predictor includes two or three control point motion vectors, and the method includes determining the control point motion vector; decoding step indices representing respective magnitudes of motion vector difference coordinates; and decoding the motion vector sign predictor index.

Aspect 6C - In aspect 5C, the method comprises determining a motion vector difference by applying a respective motion vector difference sign for each motion vector difference component to a respective magnitude of the motion vector difference component; adding the motion vector difference to each of the control point motion vectors to determine a final control point motion vector; and decoding the block of video data using the final control point motion vector.

Aspect 7C - The method of any of Aspects 1C through 6C, further comprising determining the cost using template matching.

Aspect 8C - The method of Aspect 7C, wherein the video data block is coded using an affine MMVD merge using a Merge with Motion Vector Difference (MMVD) mode, and determining the cost using the template matching comprises using a subblock-based template. It involves determining the cost using matching.

Aspect 9C - The method of any one of aspects 1C to 8C, further comprising scaling said respective magnitudes of motion vector difference components based on a picture order count (POC) difference.

Aspect 10C - The method of any of aspects 1C-9C, further comprising displaying a picture containing a decoded block of video data.

Aspect 11C - An apparatus configured to decode video data, the apparatus comprising: a memory configured to store a block of video data, and one or more processors in communication with the memory, wherein the one or more processors are configured to decode possible sign values, motion vector difference components, Constructing motion vector candidates using respective magnitudes and a motion vector predictor for a block of video data, wherein possible sign values include positive sign values and negative sign values; ; Sort the motion vector candidates based on the cost for each of the motion vector candidates to create a sorted list; determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and decode the block of video data using respective magnitudes of the motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component.

Aspect 12C - The method of aspect 11C, wherein the block of video data uses one of a merge with inter motion vector difference (MMVD) mode, an affine MMVD, a geometric partitioning mode with MMVD (GPM), or a multiple hypothesis prediction (MHP) mode. It is coded.

Aspects 13C - In aspect 12C, a block of video data is decoded using an inter MMVD mode, and the one or more processors further decode a merge index representing a motion vector predictor; decode step indices representing respective magnitudes of motion vector difference coordinates; and decode the motion vector sign predictor index.

Aspects 14C - The one or more processors of Aspect 13C further comprising: applying a respective motion vector difference sign for each motion vector difference component to a respective magnitude of the motion vector difference component to determine the motion vector difference; Add the motion vector difference to the motion vector predictor to determine the final motion vector; and configured to decode a block of video data using the final motion vector.

Aspects 15C - In aspects 12C, the block of video data is coded using an affine MMVD mode, the motion vector predictor includes two or three control point motion vectors, and the one or more processors further: decide; decode step indices representing respective magnitudes of motion vector difference coordinates; and decode the motion vector sign predictor index.

Aspects 16C - In aspects 15C, the one or more processors further comprise: applying a respective motion vector difference sign for each motion vector difference component to a respective magnitude of the motion vector difference component to determine a motion vector difference; Add the motion vector difference to each of the control point motion vectors to determine a final control point motion vector; and decode the block of video data using the final control point motion vector.

Aspect 17C - The method of any one of aspects 11C-16C, wherein the one or more processors are further configured to: determine the cost using template matching.

Aspects 18C - The method of Aspect 17C, wherein the video data block is coded using an affine MMVD merge using a Merge with Motion Vector Difference (MMVD) mode, and the one or more processors are further configured to determine the cost using template matching. , is configured to determine the cost using subblock-based template matching.

Aspect 19C - The method of any one of aspects 11C to 18C, wherein the one or more processors are further configured to scale said respective magnitudes of motion vector difference components based on a picture order count (POC) difference.

Aspect 20C - The apparatus of any one of aspects 11C-19C, further comprising a display configured to display a picture comprising a decoded block of video data.

Depending on the example, any specific acts or events of the techniques described herein may be performed in a different sequence, and may be added, merged, or removed entirely (e.g., all acts or events described It should be recognized that these techniques are not essential for implementation. Moreover, in certain examples, acts or events may be performed concurrently, for example, through multi-threaded processing, interrupt processing, or multiple processors, rather than sequentially.

In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof.　 If implemented in software, the functions may be stored or transmitted as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media refers to a computer-readable storage medium, such as a tangible medium, such as data storage media, or any device that facilitates transfer of a computer program from one place to another, e.g., according to a communication protocol. It may also include communication media including media. In this manner, computer-readable media may generally correspond to (1) a tangible computer-readable storage medium, or (2) a communication medium, such as a signal or carrier wave. 　Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementation of the techniques described in this disclosure. .　 A computer program product may include computer-readable media.

By way of example, and not limitation, such computer-readable storage media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or in the form of instructions or data structures. It may be used to store desired program code and may include any other medium that can be accessed by a computer.　 Additionally, any connection is properly termed a computer-readable medium. For example, if the Software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave. Cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, wireless, and microwave are included in the definition of medium. However, it should be understood that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transient media, but instead relate to non-transitory, tangible storage media. Disk and disc as used herein include compact disk (CD), laser disk, optical disk, digital versatile disk (DVD), floppy disk and Blu-ray disk, where disk ( A disk usually reproduces data magnetically, but a disc reproduces data optically using a laser. Combinations of the above should also be included within the scope of computer-readable media.

Instructions may be executed by one or more processors, such as one or more DSPs, general purpose microprocessors, ASICs, FPGAs, or other equivalent integrated or discrete logic circuitry. Accordingly, the terms “processor” and “processing circuitry,” as used herein, may refer to any of the foregoing structures or any other structure suitable for implementation of the techniques described herein. Additionally, in some aspects, the functionality described herein may be provided within dedicated hardware and/or software modules configured for encoding and decoding or integrated in a combined codec. Additionally, the techniques may be fully implemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC), or a set of ICs (e.g., a chip set). Various components, modules, or units are described in this disclosure to highlight functional aspects of devices configured to perform the disclosed techniques, but do not necessarily require implementation by different hardware units. Rather, as described above, the various units may be combined in a codec hardware unit or provided by a collection of interoperable hardware units, including one or more processors as described above, together with suitable software and/or firmware. It may be possible.

Various examples have been described. These and other examples are within the scope of the following claims.

Claims (20)

A method for decoding video data, comprising:
Constructing motion vector candidates using possible sign values, respective magnitudes of motion vector difference components, and a motion vector predictor for a block of video data, wherein the possible sign values are positive sign values and negative sign values. Constructing the motion vector candidates, comprising:
Sorting the motion vector candidates based on a cost for each of the motion vector candidates to create a sorted list;
determining each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and
A method of decoding video data, comprising decoding the block of video data using respective magnitudes of motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component. According to claim 1,
The block of video data is coded using one of the following: Merge Intermotion Vector Differences (MMVD) mode, affine MMVD, Geometric Partitioning Mode (GPM), or Multiple Hypothesis Prediction (MHP) mode. method. According to claim 2,
The block of video data is coded using inter MMVD mode,
The method is:
decoding a merge index representing the motion vector predictor;
decoding a step index representing the respective magnitudes of motion vector difference coordinates; and
The method of decoding video data further comprising decoding the motion vector sign predictor index. According to claim 3,
applying the respective motion vector difference sign for each motion vector difference component to the respective magnitudes of the motion vector difference components to determine a motion vector difference;
adding the motion vector difference to the motion vector predictor to determine a final motion vector; and
The method of decoding video data further comprising decoding the block of video data using the final motion vector. According to claim 2,
The block of video data is coded using an affine MMVD mode, and the motion vector predictor includes two or three control point motion vectors,
The method is:
determining the control point motion vectors;
decoding a step index representing the respective magnitudes of motion vector difference coordinates; and
The method of decoding video data further comprising decoding the motion vector sign predictor index. According to claim 5,
The method is:
applying the respective motion vector difference sign for each motion vector difference component to the respective magnitudes of the motion vector difference components to determine a motion vector difference;
adding the motion vector difference to each of the control point motion vectors to determine final control point motion vectors; and
Decoding the block of video data using the final control point motion vectors. According to claim 1,
A method for decoding video data, further comprising determining the cost using template matching. According to claim 7,
The video data block is coded using affine MMVD merging using Merge with Motion Vector Difference (MMVD) mode, and determining the cost using the template matching includes determining the cost using subblock-based template matching. A method of decoding video data, comprising determining: According to claim 1,
The method of decoding video data further comprising scaling said respective sizes of motion vector difference components based on a picture order count (POC) difference. According to claim 1,
A method for decoding video data, further comprising displaying a picture containing a decoded block of video data. A device configured to decode video data, comprising:
A memory configured to store blocks of video data; and
comprising one or more processors in communication with the memory,
The one or more processors:
Constructing motion vector candidates using possible sign values, respective magnitudes of motion vector difference components, and a motion vector predictor for a block of video data, wherein the possible sign values have a positive sign value and a negative sign value. Constructing the motion vector candidates, including;
sort the motion vector candidates based on a cost for each of the motion vector candidates to create a sorted list;
determine each motion vector difference sign for each motion vector difference coordinate based on the motion vector sign predictor index and the sorted list; and
An apparatus configured to decode video data, configured to decode the block of video data using respective magnitudes of motion vector difference coordinates and a respective motion vector difference sign for each motion vector difference component. According to claim 11,
To decode video data, the blocks of video data are coded using one of the following: Merge Intermotion Vector Differences (MMVD) mode, affine MMVD, Geometric Partitioning Mode (GPM), or Multiple Hypothesis Prediction (MHP) mode. Configured device. According to claim 12,
The block of video data is coded using an inter MMVD mode, and the one or more processors further:
decode the merge index representing the motion vector predictor;
decode a step index representing the respective magnitudes of motion vector difference coordinates; and
An apparatus configured to decode video data, configured to decode the motion vector sign predictor index. According to claim 13,
The one or more processors further:
apply the respective motion vector difference sign for each motion vector difference component to the respective magnitudes of the motion vector difference components to determine a motion vector difference;
add the motion vector difference to the motion vector predictor to determine a final motion vector; and
An apparatus configured to decode video data, and configured to decode the block of video data using the final motion vector. According to claim 12,
The block of video data is coded using an affine MMVD mode, the motion vector predictor includes two or three control point motion vectors, and the one or more processors further:
determine the control point motion vectors;
decode a step index representing the respective magnitudes of motion vector difference coordinates; and
An apparatus configured to decode video data, configured to decode the motion vector sign predictor index. According to claim 15,
The one or more processors further:
apply the respective motion vector difference sign for each motion vector difference component to the respective magnitudes of the motion vector difference components to determine a motion vector difference;
adding the motion vector difference to each of the control point motion vectors to determine final control point motion vectors; and
An apparatus configured to decode video data, configured to decode the block of video data using the final control point motion vectors. According to claim 11,
wherein the one or more processors are further configured to determine the cost using template matching. According to claim 17,
The video data block is coded using affine MMVD merging using Merge with Motion Vector Difference (MMVD) mode, and to determine a cost using the template matching, the one or more processors further: An apparatus configured to decode video data, and configured to determine the cost using matching. According to claim 11,
wherein the one or more processors are further configured to scale the respective magnitudes of motion vector difference components based on a picture order count (POC) difference. According to claim 11,
An apparatus configured to decode video data, further comprising a display configured to display a picture comprising a decoded block of video data.