CN118301370B - Wavelet fast transformation method for JPEG-XS encoding and decoding - Google Patents
Wavelet fast transformation method for JPEG-XS encoding and decoding Download PDFInfo
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Abstract
The invention relates to a wavelet rapid transformation method for JPEG-XS encoding and decoding, which comprises the following steps: dividing frame data to generate a wavelet unit; vertical horizontal wavelet transform; distinguishing and respectively processing; a half-image width horizontal wavelet transform; three wavelet transforms. The invention reclassifies the data of a JPEG-XS coding image according to the characteristics of the coding flow, and carries out vertical-horizontal wavelet transformation on all image data in the original coding process; and then carrying out vertical-horizontal wavelet transformation or horizontal wavelet transformation on the 1/4 image, and optimizing the flow of carrying out three times of horizontal wavelet transformation. The buffer memory of the intermediate transformation result is reduced by adopting a blocking mode, the reading and writing of intermediate data are also reduced, and the coding efficiency is greatly improved. The data driving DWT mode can further reduce the buffer memory and the read-write of intermediate data, thereby improving the coding efficiency.
Description
Technical Field
The invention relates to a wavelet rapid transformation method for JPEG-XS encoding and decoding, which is a data transmission method of a computer network and is a method for processing and transmitting network ultra-high definition video data.
Background
JPEG-XS is the latest international standard based on the shallow compression domain of wavelet compression technology, capable of generating higher quality images with low latency. The JPEG-XS can record 8K (7680 multiplied by 4320), 4K (3840 multiplied by 2160) and HD (1920 multiplied by 1080) 422-10 bit videos with reasonable code rate, has the characteristics of visual lossless quality, good multi-generation replication characteristic, low coding and decoding complexity, low delay of coding and decoding and the like, accords with the dual requirements of broadcasting and television programs on low delay and high quality, and can obviously reduce the pressure of ultra-high definition business on data storage, streaming transmission and video processing calculation. The JPEG-XS coding uses the coding techniques of wavelet transformation, quantization, entropy coding, etc., the wavelet transformation firstly carries out vertical transformation processing on the column data of the image, then stores the intermediate result of the column processing, and then carries out horizontal transformation on the data, which at least needs the intermediate storage space of one frame of data, and the storage space required under 8K 422 10bit is about 200Mb, which needs a large capacity memory to buffer the column transformation result, thus wasting a great amount of storage resources, increasing the expenditure of reading and writing data, increasing the storage expenditure, reducing the utilization rate of hardware and limiting the speed of encoding and decoding. On the other hand, with the continuous development of information technology, the advantage of parallel processing of mass data on the memory bandwidth is more and more obvious. However, the parallel processing is difficult due to the vertical wavelet transform of JPEG-XS coding, and meanwhile, the vertical transform operates the column data, so that the characteristic of uncorrelation of the inter-slice coding cannot be fully utilized, the potential of parallel coding is not exerted, and the coding efficiency is affected. There is a need to find an efficient implementation method for DWT/IDWT of JPEG-XS codec.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a wavelet fast transformation method for JPEG-XS encoding and decoding. Based on the structural characteristics of JPEG-XS frames, the method adopts a blocking mode to reduce the buffer of intermediate transformation results, also reduces the reading and writing of intermediate data, and greatly improves the coding efficiency. The data driving DWT mode can further reduce the buffer memory and the read-write of intermediate data, thereby improving the coding efficiency.
The purpose of the invention is realized in the following way: a wavelet fast transformation method for JPEG-XS codec, the steps of the method being as follows:
Step 1, a frame data division wavelet transformation unit: dividing frame data according to coding parameters, dividing the frame data into a plurality of pixel blocks with the size of frame_width multiplied by K multiplied by 2 v, and taking the pixel blocks as a wavelet transformation unit, wherein the frame_width is the image pixel width, v is the number of vertical wavelet decomposition times, K is a positive integer, the maximum value is frame_width/2 v, the frame_height is the image pixel height, and 2 v is the pixel height of precinct;
Step 2, first or second vertical-horizontal wavelet transform: dividing the wavelet transformation unit in the step 1 into 8×8 pixel blocks, performing vertical wavelet transformation from right to left and from top to bottom, and taking the transformation result as input data; then checking whether the input data is enough to perform horizontal wavelet transformation, returning to repeat the vertical wavelet transformation if the input data is insufficient, and performing the horizontal wavelet transformation if the input data is enough; the wavelet coefficient generated by each 8×8 pixel block after twice transformation can be divided into four sub-bands, which are LL, HL, LH, HH respectively; wherein LL represents low-frequency components in the horizontal and vertical directions of the image, HH represents high-frequency components in the horizontal and vertical directions of the image, LH represents low-frequency components in the horizontal and vertical directions of the image, and HL represents high-frequency and low-frequency components in the horizontal and vertical directions of the image; classifying and storing all four sub-band coefficients, outputting LL sub-band coefficients, and preparing to continue wavelet transformation;
Step 3, distinguishing and respectively processing: if the map Profile is the Main Profile, directly jumping to the step 4; if the High Profile is High, repeating the step 2 with the LL wavelet coefficient calculated in the step 2, and then skipping the step 4 to directly carry out the step 5;
Step 4, horizontal wavelet transformation of half image width: checking whether the LL data is enough to perform the horizontal wavelet transformation once, if not, returning to the step 2, otherwise, performing the horizontal transformation; the transform result may be divided into two subbands, LL and HL; all LL sub-band data and HL sub-bands are respectively stored in sequence, LL sub-band coefficients are output, and wavelet transformation is prepared to be continued;
Step 5, three times of horizontal wavelet transformation: checking whether the input data is enough to perform three times of horizontal wavelet transformation, returning to the step 2 if the input data is insufficient, otherwise performing the horizontal transformation; the transform result may be divided into two subbands, LL and HL; all LL sub-band data and HL sub-bands are respectively stored in sequence; the LL sub-band data is used as the input of the next transformation, the output still needs to be classified and stored according to the sequence, and the transformation data needed by the entropy coding is finally obtained after repeating for three times.
The invention has the advantages and beneficial effects that: the invention reclassifies the data of a JPEG-XS coding image according to the characteristics of the coding flow, and carries out vertical-horizontal wavelet transformation on all image data in the original coding process; and then carrying out vertical-horizontal wavelet transform (High Profile) or horizontal wavelet transform (Main Profile) on the 1/4 image, and optimizing the flow of carrying out three times of horizontal wavelet transform. The optimized coding process can respectively code the minimum coding units, namely slices, so that a large number of intermediate results are prevented from being stored, the overhead of hardware is reduced, and the utilization rate of the hardware is improved. The wavelet transformation mode in the prior art caches a large amount of intermediate transformation data, and simultaneously introduces the reading and writing of the data, which is a main bottleneck of the coding performance of the current CPU architecture. The invention adopts a blocking mode to carry out DWT on the image pixels, reduces the buffer memory of the intermediate transformation result in a blocking mode, also reduces the reading and writing of intermediate data, and greatly improves the coding efficiency. The invention also adopts a data driving mode to carry out DWT, the data output by each time of transformation is used as the input data of the next-stage DWT transformation, and the next-stage DWT transformation starts transformation and outputs when detecting that enough input data exists until all data is transformed. The data driving DWT mode can further reduce the buffer memory and the read-write of intermediate data, thereby further improving the coding efficiency.
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The invention is further described below with reference to the drawings and examples.
FIG. 1 is a flowchart of a JPEG-XS encoding process;
FIG. 2 is a schematic diagram of a wavelet transform process of JPEG-XS;
FIG. 3 is a wavelet decomposition diagram of High Profile;
FIG. 4 is a schematic diagram of a JPEG-XS frame structure;
Fig. 5 is a flow chart of a method according to an embodiment of the invention.
Detailed Description
Examples:
the embodiment is a wavelet fast transformation method for JPEG-XS encoding and decoding.
JPEG-XS uses DWT, quantization, entropy coding, etc. coding techniques, and the encoding and decoding of each frame does not need to refer to other frames. The encoding process flow diagram is shown in fig. 1. JPEG-XS defines different profiles in order to allow different levels of latency and complexity, each Profile having a maximum number of vertical wavelet decomposition defined as follows:
Light Profile horizontal 5-layer decomposition, vertical 0-layer decomposition
Main Profile horizontal 5-layer decomposition and vertical 1-layer decomposition
High Profile horizontal 5-layer decomposition, vertical 2-layer decomposition
Since LightProfile does not require a vertical transformation, there is no problem as described above, and therefore the data partitioning of this profile in step 1 is relatively simple, but the benefits of the present invention can still be obtained using only a data-driven approach during a horizontal transformation. The wavelet transform in the JPEG-XS encoding process is shown in FIG. 2, taking HighProfile as an example, firstly performing one vertical transform on all column data in sequence, and performing one horizontal transform on all lines of the transform result. The LL band subjected to the vertical transform and the horizontal transform, respectively, is repeated once more, and then the horizontal transform is recycled 3 times for each line in the LL band result. A total of 2 vertical transforms and 5 horizontal transforms were performed, the final results of the transforms are shown in fig. 3. The type of band obtained by the transformation is shown in table 1. For the whole image, each pixel generates a corresponding wavelet coefficient, and finally outputs and inputs coefficient matrixes with the same size for quantization, entropy coding and the like of subsequent coding.
| 0 | LL5,2 |
| 1 | HL5,2 |
| 2 | HL4,2 |
| 3 | HL3,2 |
| 4 | HL2,2 |
| 5 | LH2,2 |
| 6 | HH2,2 |
| 7 | HL1,1 |
| 8 | LH1,1 |
| 9 | HH1,1 |
Table 1 High Profile correspondence of each band after wavelet transform
The minimum coding unit of the JPEG-XS format is slice, which consists of a number precinct of precinct, the width of which is typically the width of the image, and the height of which is 2 v (v is the number of vertical decomposition layers). Taking the 8K resolution High Profile as an example, precinct has a width 7680 pixels and a height of 4 pixels. Inside a slice, the lower precinct can make predictions with the upper precinct; the slices are independent of each other. The frame structure of JPEG-XS is shown in FIG. 4, where the slice height is 4 precinct, horizontal 5-level decomposition, vertical 2-level decomposition. The middle bold line represents precinct boundaries and the bold line represents image boundaries. Precinct with dashed and thin lines belong to different slices, respectively.
From the wavelet transform process of JPEG-XS coding, it can be found that the vertical transform and the horizontal transform respectively need to be calculated for one column and one row of image data, and the calculation results need to be saved in a buffer for the following transform. On the one hand, the parallel coding among slices is affected, the structural characteristics of JPEG-XS are not fully utilized, and on the other hand, a large amount of storage space and read-write time are consumed, so that the coding efficiency is affected.
According to the characteristic of the JPEG-XS coding image structure, the embodiment designs and realizes an efficient wavelet transformation method, and greatly improves the coding efficiency. Meanwhile, JPEG-XS decoding is the inverse operation of the encoding process, and IDWT in decoding is the inverse process of DWT, and the transformation method described in this embodiment can also be used for the IDWT of JPEG-XS to improve decoding efficiency.
The existing wavelet transformation firstly carries out vertical and horizontal wavelet transformation on all image data, then carries out vertical and horizontal wavelet transformation (High Profile) or horizontal wavelet transformation (Main Profile) on 1/4 image, and then carries out the third horizontal wavelet transformation, and each time wavelet transformation needs to be stored, thereby increasing the hardware cost.
This flow is optimized in this embodiment. The optimized coding process can respectively code the minimum coding units, namely slices, so that a large number of intermediate results are prevented from being stored, the overhead of hardware is reduced, and the utilization rate of the hardware is improved.
The encoding process in this embodiment is that data of a JPEG-XS encoded image is first re-divided according to the characteristics of the encoding process by adopting a data driving manner, and then divided into a wavelet transform unit and a pixel block, and then wavelet transform is performed according to different profiles, so as to save access hardware overhead in the wavelet transform process.
The wavelet fast transformation method of JPEG-XS codec of the present embodiment includes the following steps, the flow of which is shown in FIG. 5:
Step 1, a frame data division wavelet transformation unit: the frame data is divided according to coding parameters, and the frame data is divided into a plurality of pixel blocks with the size of frame_width multiplied by K multiplied by 2 v, and the pixel blocks are used as wavelet transformation units, wherein frame_width is the image pixel width, v is the number of vertical wavelet decomposition times, K is a positive integer, the maximum value is frame_height/2 v, at the moment, the whole image is represented as a transformation unit, frame_height is the image pixel height, and 2 v is the pixel height of precinct.
The value of K needs to take into account the number precinct of slices contained in the coding structure. Then, the image size of 8K is 7680× 4320,High Profile v =2, and the maximum value of K is 1080. If each slice contains 4 precinct, the smallest wavelet transform unit is 7680x4 x 2 2, 7680x16; v=1 for 8K Main Profile, where K is a maximum value of 2160. If each slice contains 4 precinct, the smallest wavelet transform unit is 7680x4 x 2 1, 7680x8. Light Profile is ignored because it does not require vertical wavelet decomposition.
The method comprises the steps of firstly dividing a frame of image into a plurality of pixel blocks, wherein the division is mainly based on the frame structure of JPEG-XS and the characteristics of a CPU. For example, an image may be divided into 10 wavelet cells, each wavelet cell containing 7680×432 pixels.
Step 2, first or second vertical-horizontal wavelet transform: dividing the wavelet transformation unit in the step 1 into 8×8 pixel blocks, performing vertical wavelet transformation from right to left and from top to bottom, and taking the transformation result as input data; then checking whether the input data is enough to perform horizontal wavelet transformation, returning to repeat the vertical wavelet transformation if the input data is insufficient, and performing horizontal transformation if the input data is enough; the wavelet coefficient generated by each 8×8 pixel block after twice transformation can be divided into four sub-bands, which are LL, HL, LH, HH respectively; wherein LL represents low-frequency components in the horizontal and vertical directions of the image, HH represents high-frequency components in the horizontal and vertical directions of the image, LH represents low-frequency components in the horizontal and vertical directions of the image, and HL represents high-frequency and low-frequency components in the horizontal and vertical directions of the image; all four subband coefficients are classified and stored, LL subband coefficients are output, and wavelet transformation is ready to continue.
Note that the wavelet transform unit is divided by 8×8, and the transform needs to use pixels of adjacent blocks.
Step 3, distinguishing and respectively processing: if the map Profile is the Main Profile, directly jumping to the step 4; if the High Profile is High, repeating the step 2 with the LL wavelet coefficient calculated in the step 2, and then skipping the step 4 to directly carry out the step 5.
Step 4, horizontal wavelet transformation of half image width: checking whether the LL data is sufficient to perform a horizontal wavelet transform once, if not, returning to step 2, and if so, performing a horizontal transform; the transform result may be divided into two subbands, LL and HL; all LL subband data and HL subbands are respectively stored in sequence, LL subband coefficients are output, and the wavelet transformation is ready to be continued.
Steps 3 and 4 may be passed if the embodiment is described for a high profile.
Step 5, three times of horizontal wavelet transformation: it is checked whether the input data is sufficient to perform three horizontal wavelet transforms, and if not, step 2 is returned, otherwise, horizontal transforms are performed. The transform result may be divided into two subbands, LL and HL; all LL sub-band data and HL sub-bands are respectively stored in sequence; the LL sub-band data is used as the input of the next transformation, the output still needs to be classified and stored according to the sequence, and the transformation data needed by the entropy coding is finally obtained after repeating for three times.
The wavelet transformation process adopts a data-driven mode to carry out DWT: in the whole transformation process, except the first vertical transformation, the data output by each transformation is used as the input data of the next-stage DWT transformation, the next-stage DWT transformation starts transformation after detecting enough input data, and the transformation is output until all the data are transformed.
Finally, it should be noted that the foregoing is merely illustrative of the technical solution of the present invention and not limiting, and although the present invention has been described in detail with reference to the preferred arrangement, it will be understood by those skilled in the art that modifications and equivalent substitutions may be made to the technical solution of the present invention (such as the manner of partitioning, the manner of wavelet transform, the sequence of steps, etc.), without departing from the spirit and scope of the technical solution of the present invention.
Claims (1)
1. A wavelet fast transformation method for JPEG-XS codec, characterized by the steps of:
Step 1, a frame data division wavelet transformation unit: dividing frame data according to coding parameters, dividing the frame data into a plurality of pixel blocks with the size of frame_width multiplied by K multiplied by 2 v, and taking the frame_width as a wavelet transformation unit, wherein the frame_width is the image pixel width, v is the number of vertical wavelet decomposition times, K is a positive integer, the maximum value of K is frame_height/2 v, the frame_height is the image pixel height, and 2 v is the pixel height of precinct;
Step 2, first or second vertical-horizontal wavelet transform: dividing the wavelet transformation unit in the step 1 into 8×8 pixel blocks, performing vertical wavelet transformation from right to left and from top to bottom, and taking the transformation result as input data; then checking whether the input data is enough to perform horizontal wavelet transformation, returning to repeat the vertical wavelet transformation if the input data is insufficient, and performing the horizontal wavelet transformation if the input data is enough; the wavelet coefficient generated by each 8×8 pixel block after twice transformation can be divided into four sub-bands, which are LL, HL, LH, HH respectively; wherein LL represents low-frequency components in the horizontal and vertical directions of the image, HH represents high-frequency components in the horizontal and vertical directions of the image, LH represents low-frequency components in the horizontal and vertical directions of the image, and HL represents high-frequency and low-frequency components in the horizontal and vertical directions of the image; classifying and storing all four sub-band coefficients, outputting LL sub-band coefficients, and preparing to continue wavelet transformation;
Step 3, distinguishing and respectively processing: if the map Profile is the Main Profile, directly jumping to the step 4; if the High Profile is High, repeating the step 2 with the LL wavelet coefficient calculated in the step 2, and then skipping the step 4 to directly carry out the step 5;
Step 4, horizontal wavelet transformation of half image width: checking whether the LL data is enough to perform the horizontal wavelet transformation once, if not, returning to the step 2, otherwise, performing the horizontal transformation; the transform result may be divided into two subbands, LL and HL; all LL sub-band data and HL sub-bands are respectively stored in sequence, LL sub-band coefficients are output, and wavelet transformation is prepared to be continued;
Step 5, three times of horizontal wavelet transformation: checking whether the input data is enough to perform three times of horizontal wavelet transformation, returning to the step 2 if the input data is insufficient, otherwise performing the horizontal transformation; the transform result may be divided into two subbands, LL and HL; all LL sub-band data and HL sub-bands are respectively stored in sequence; the LL sub-band data is used as the input of the next transformation, the output still needs to be classified and stored according to the sequence, and the transformation data needed by the entropy coding is finally obtained after repeating for three times.
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