JP5143033B2 - Image processing apparatus and method - Google Patents

Description

  The present invention relates to an image processing apparatus and method for detecting and removing a noise part included in an image obtained by decoding image data that has been subjected to lossy compression coding, for example, by the MPEG (Moving Picture Experts Group) method. .

  Conventionally, as an image encoding method, an intra-frame encoding method such as Motion JPEG or Digital Video, or H.264 using inter-frame predictive encoding is used. 261, H.M. H.263, MPEG-1, and MPEG-2 are known. In recent years, H.C. An encoding method such as H.264 is employed. These encoding methods are internationally standardized by ISO (International Organization for Standardization) and ITU (International Telecommunication Union).

  MPEG-2, which is a typical encoding method, is called lossy encoding, and even if encoded image data is decoded, it does not completely return to the original image data. This is because quantization is performed after DCT transform at the time of encoding. These encoding methods use the statistical properties of the image signal and reduce the amount of information by removing the redundancy contained in the signal. That is, since human vision is insensitive to the high-frequency component of the image, the high-frequency component is roughly quantized to eliminate redundancy and obtain high coding efficiency.

However, in lossy encoding that performs this type of DCT transform, data compression is performed by limiting high-frequency components, so noise called mosquito noise occurs around the edge of the image or around the moving object. As a result, the image quality of the restored image is degraded. A method for reducing this mosquito noise has been proposed. For example, a method has been proposed in which an edge portion of an input image signal is detected and the edge portion of the image signal is filtered by a noise removal filter to reduce mosquito noise and obtain an image signal. As an example, Patent Document 1 proposes to detect horizontal and vertical edges after detecting a motion vector, and then apply a filter in each dimension.
Japanese Patent Laid-Open No. 10-13718

  However, in the above conventional technique, the mosquito noise removal filtering process is performed at the edge portion of the image signal regardless of the presence or absence of the mosquito noise in the image signal. Therefore, the image is deteriorated in the portion where the mosquito noise is not generated. End up. In addition, when there is a texture area including a fine edge, this area is erroneously determined as an edge, and the texture information is deleted to deteriorate the image quality.

  These problems are the noise removal processing at the edge of the image signal without accurately detecting the noise generation part such as mosquito noise included in the image data obtained by decoding the frequency converted and lossy compression encoded image data. It was caused by giving. Furthermore, when there is a process such as IP conversion for converting an interlace signal into a progressive signal after the noise removal process, it is necessary to remove the noise so as not to adversely affect the process. In other words, noise must be removed while maintaining interlace information.

  An object of the present invention is to solve the conventional problems described above.

  The object of the present invention is to detect and delete a noise generating part such as mosquito noise included in decoded image data obtained by decoding an image stream generated by performing frequency conversion and lossy compression coding. The solution is to solve the problem.

In order to achieve the above object, an image processing apparatus according to an aspect of the present invention has the following arrangement. That is,
An image processing apparatus for removing noise components of decoded image data obtained by decoding an image stream generated by lossy encoding,
Horizontal edge strength measuring means for measuring the strength of the horizontal edge of each block of the input frame;
Vertical edge strength measuring means for measuring the strength of the vertical edge of each block of the input frame;
Edge strength storage means for storing horizontal and vertical edge strengths measured by the horizontal edge strength measurement means and the vertical edge strength measurement means;
Noise removal flag calculation means for calculating a noise removal flag for identifying a block from which noise should be removed based on the horizontal and vertical edge strengths stored in the edge strength storage means;
Noise removal flag storage means for storing the noise removal flag calculated by the noise removal flag calculation means;
Filter control means for outputting a control signal for controlling a filter for performing noise removal based on the input edge strength of the current frame, the edge strength of the immediately preceding frame stored in the edge strength storage means, and the noise removal flag;
Have a filtering means for performing filtering processing on the current frame in response to the control signal from the filter control means,
The filter control means includes
The edge strength of the block of the current frame measured by the horizontal edge strength measurement means and the vertical edge strength measurement means, and the edge of the block corresponding to the block of the current frame of the immediately preceding frame stored in the edge strength storage means The filter strength is calculated based on the product of the difference between the strength and the strength multiplier of the filter strength, and the control signal for the block from which the noise is to be removed is output .

In order to achieve the above object, an image processing method of an image processing apparatus according to an aspect of the present invention includes the following steps. That is,
An image processing method of an image processing apparatus for removing a noise component of decoded image data obtained by decoding an image stream generated by lossy encoding,
A horizontal edge strength measurement process for measuring the strength of the horizontal edge of each block of the input frame;
A vertical edge strength measurement step for measuring the strength of the vertical edge of each block of the input frame;
An edge strength storing step for storing horizontal and vertical edge strengths measured in the horizontal edge strength measuring step and the vertical edge strength measuring step;
A noise removal flag calculation step for calculating a noise removal flag for identifying a block from which noise is to be removed based on the horizontal and vertical edge strengths stored in the edge strength storage step;
A noise removal flag storage step for storing the noise removal flag calculated in the noise removal flag calculation step;
A filter control step for outputting a control signal for controlling a filter for performing noise removal based on the input edge strength of the current frame, the edge strength of the immediately preceding frame stored in the edge strength storage step, and the noise removal flag;
Said have a filter step of performing filtering processing for the current frame in response to said control signal output by the filter control step,
In the filter control step,
The edge strength of the block of the current frame measured in the horizontal edge strength measurement step and the vertical edge strength measurement step, and the edge of the block corresponding to the block of the current frame in the immediately preceding frame stored in the edge strength storage step The filter strength is calculated based on the product of the difference between the strength and the strength multiplier of the filter strength, and the control signal for the block from which the noise is to be removed is output .

  ADVANTAGE OF THE INVENTION According to this invention, the noise generation part contained in the decoded image data which decoded the image stream produced | generated by performing frequency conversion and lossy compression encoding can be detected, and the noise can be removed.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments do not limit the present invention according to the claims, and all combinations of features described in the embodiments are not necessarily essential to the solution means of the present invention. .

  FIG. 1 is a block diagram showing a configuration of a main part of an image processing apparatus according to an embodiment of the present invention. An object of the image processing apparatus according to the present embodiment is to input decoded image data obtained by decoding an image stream generated by lossy encoding, and to remove noise components from the input frame. Here, the unit of image data processing is 4 × 4 pixels, and this is referred to as a target block (hereinafter referred to as a block).

  The horizontal edge strength measuring device 100 inputs one block of the luminance signal and measures the horizontal edge strength. In the present embodiment, the edge strength for the pixels of the block in the processing unit is set as the cumulative value of the Sobel filter.

  2A and 2B are diagrams illustrating an example of an operator of a Sobel filter used in this embodiment.

  2A shows an example of an operator of a horizontal Sobel filter, and FIG. 2B shows an example of an operator of a vertical Sobel filter.

  The vertical edge strength measuring device 101 inputs one block of the luminance signal and measures the vertical edge strength. The edge strength memory (edge strength storage unit) 102 stores the horizontal and vertical edge strengths measured by the horizontal edge strength measuring device 100 and the vertical edge strength measuring device 101 for one frame each. The edge strength memory 102 has a two-bank configuration, and can input to one bank and simultaneously output to the other bank. This bank switching is performed every frame processing.

  The noise removal flag calculator 103 calculates a noise removal flag for specifying a region to be subjected to noise removal from the edge strength stored in the edge strength memory 102. The noise removal flag memory (noise removal flag storage unit) 104 stores the noise removal flag calculated by the noise removal flag calculator 103 for one frame. The noise removal flag memory 104 has a two-bank configuration, and can be input to one bank and output from the other bank at the same time. This bank switching is performed every frame processing. The filter strength multiplier table 105 refers to the filter strength multiplier from the edge strength change value described later.

  FIG. 3 is a diagram illustrating an example of the relationship between the edge strength change value and the filter strength multiplier.

  This curve tends to increase the filter strength when the edge strength change value is low.

  A filter strength calculator (filter control unit) 106 is described later based on the horizontal and vertical edge strengths of the current frame, the edge strength of the immediately preceding frame, the noise removal flag of the immediately preceding frame, and the filter strength basic multiplier input from the outside. Calculate the strength of the filter. The horizontal and vertical edge strengths of the current frame are obtained from the horizontal edge strength measuring device 100 and the vertical edge strength measuring device 101. Further, the edge strength of the immediately preceding frame is obtained from the edge strength memory 102, and the noise removal flag of the immediately preceding frame is stored in the noise removal flag memory 104. In calculating the filter strength, the filter strength multiplier table 105 is referred to.

  The filter 107 is a filter that executes a two-dimensional (hereinafter referred to as 2D) filtering process in a frame in accordance with a control signal from the filter strength calculator 106. In the present embodiment, the filter 107 uses an ε filter.

  FIG. 4 is a diagram showing an example of this ε filter.

  In this filter processing, the difference value between the center pixel f (x, y) and its neighboring pixels f (x + i, y + j), (x, y = −M,..., 0, 1,..., M) is calculated. If the absolute value is calculated and greater than ε, the value of the neighboring pixel is replaced with the value of the central pixel, and smoothing processing is performed. As a result, the edge component can be protected at g (x, y), and noise that is a harmonic having a small amplitude can be smoothed and suppressed. The details of this ε filter are referred to the following document.

[Literature Hiroshi Harashima et al. “Ε-Separation Nonlinear Digital Filter and Its Applications” IEICE 57-146 [A-36] April 1982
Next, the operation of the main part of the image processing apparatus of FIG. 1 will be described with reference to the flowcharts of FIGS. In the present embodiment, the processing is switched between the first frame and the other frames.

  FIG. 5 is a flowchart for explaining processing of the first frame.

  First, in step S1, the horizontal edge strength measuring instrument 100 measures the horizontal edge strength. In step S2, the vertical edge strength measuring device 101 measures the strength of the vertical edge. In step S 3, the horizontal edge strength and the vertical edge strength value are stored in the edge strength memory 102. The order of measuring the strength of the horizontal edge and the strength of the vertical edge is not limited to this, and the strength of the vertical edge may be measured first or may be performed in parallel.

  In step S4, the noise removal flag calculator 103 creates a noise removal flag map based on the edge strength stored in the edge strength memory 102. In step S 5, the calculated noise removal flag map is stored in the removal flag memory 104. In step S6, the banks of the edge strength memory 102 and the noise removal flag memory 104 are switched. In the next frame, the stored bank is read and stored in the other bank.

  By the processing described above, only the storage processing to the two maps is performed in the first frame, and the noise removal processing is not performed.

  Next, processing in normal frames after the first frame will be described using the flowchart of FIG.

  FIG. 6 is a flowchart for explaining processing of frames after the first frame.

  The processing in steps S11 to S13 in FIG. 6 is the same as that in steps S1 to S3 in FIG.

  Thus, after the edge strength of the current frame is stored in the edge strength memory 102 in step S13, the edge strength for each block of the immediately preceding frame stored in the edge strength memory 103 is acquired in step S14. In step S15, the noise removal flag for each block of the immediately preceding frame stored in the noise removal flag memory 104 is acquired.

In step S16, the horizontal filter and vertical filter strengths are calculated from the two pieces of map information of the immediately preceding frames. In step S17, the filter 107 is controlled by the control signal to execute a filtering process for noise removal. In step S18, a noise removal flag map is generated.
In steps S19 and S20, the calculated noise removal flag map is stored in the noise removal flag memory 104 in the same manner as in steps S5 and S6 in FIG. Switch.

  Next, a method of generating a noise removal flag map will be described with reference to FIG.

  FIG. 7 is a flowchart illustrating a method of generating a noise removal flag map according to the present embodiment.

  First, in step S31, the horizontal and vertical edge strengths of the previous frame that have already been stored are added to calculate the edge strength of the previous frame. In step S32, a block (first block) having an edge strength larger than the predetermined value EP1 is extracted from the measured and stored edge strength map. Next, the process proceeds to step S33, and the edge strengths of the neighboring eight blocks adjacent to the block having the large edge strength are measured. In step S34, a block (second block) having an edge strength lower than the predetermined value EP2 in the eight surrounding blocks is determined as an extended block region not including a block having a high edge strength. Next, the process proceeds to step S35, and the extended block area thus obtained is stored in the noise removal flag memory 104 as a block with the noise removal flag turned on and other blocks as blocks with the noise removal flag turned off. In addition, for a block whose noise removal flag is on, a difference value between the edge strength of the expanded block and the edge strength of the expansion source block is stored.

  Next, a method for calculating the strength of the filter 107 will be described with reference to FIG.

  FIG. 8 is a flowchart for explaining the intensity calculation method of the filter 107 according to this embodiment. The block to be processed here is a block whose noise removal flag is on.

  First, in step S41, the horizontal and vertical edge strengths of each block of the immediately preceding frame already stored in the edge strength memory 102 are added to calculate the edge strength of each block of the immediately preceding frame. In step S42, the horizontal and vertical edge strengths of the corresponding blocks of the current frame output from the horizontal edge strength measuring device 100 and the vertical edge strength measuring device 101 are added to obtain the edge strength of the corresponding block of the current frame. calculate. In step S43, the calculated edge strength of the block of the immediately preceding frame and the edge strength change value DE of the corresponding block of the current frame are calculated, and an operation using the multiplier table is performed to filter the block. Calculate the intensity.

Filter strength = DE x W (DE) x WD
Here, the edge strength change value DE indicates (preceding frame edge strength) − (current frame edge strength). W (DE) represents the filter strength multiplier at the time of DE, and WD represents the filter strength basic multiplier of the external input. The filter strength is a value that does not exceed a predetermined minimum value and maximum value.

  FIG. 9 is a diagram for explaining a specific example (A) of extending the edge region of the immediately preceding frame and an example (B) until determining the noise removal target block of the current frame.

  In the frame immediately before FIG. 9A, a block 900 having an edge strength higher than the specified value EP1 is selected. Then, the area is expanded to the block 901 in which the edge strength is extremely reduced and the edge strength is equal to or less than the specified value EP2. The block indicated by 901 is a target block for subsequent processing.

  Next, similarly in FIG. 9B, a block 910 having an edge strength higher than the specified value EP1 is selected. Then, the area is expanded to the block 911 in which the edge strength is extremely reduced and the edge strength is equal to or less than the specified value EP2. Next, the edge strength of the immediately preceding frame is compared with the edge strength of the current frame, and if the difference is equal to or less than TH1, the block area is a noise removal target (the hatched line is added in the block indicated by 911). Block). On the other hand, when the difference is larger than TH1 and the edge strength is increased or decreased, it is excluded from the noise removal target block (block marked with “x” in the block indicated by 911).

  In the above-described embodiment, the processing target block is 4 × 4 pixels. However, other sizes such as 8 × 4, 4 × 8, and 8 × 8 pixels may be used.

  Further, although the Sobel filter is used in the processing in the edge intensity measuring devices 100 and 101, other differential filters may be used.

  The filter 107 is an ε filter, but other edge preserving filters may be used.

  Furthermore, the threshold values EP1 and EP2 in the noise removal flag calculator 103 may be set variably for each frame.

  As described above, according to the present embodiment, it is possible to accurately detect a portion where coding noise such as mosquito noise included in image data is generated and to adaptively switch between horizontal and 2D filters. The present invention provides a simple means capable of performing noise removal processing while maintaining the state of the interlace signal.

<Other embodiments>
FIG. 10 is a block diagram illustrating the hardware configuration of the image processing apparatus according to the above-described embodiment.

  A central processing unit (CPU) 1000 controls the entire computer and performs various processes. A memory 1001 is a memory that provides an operating system (OS), software, data, and a storage area necessary for calculation necessary for operation control of the image processing apparatus. It is also used as a work area when the CPU 1000 performs various control processes. Therefore, each processing step in the flowchart described above is realized by the cooperation of the program stored in the memory 1001 and the CPU 1000. A system bus 1002 connects the CPU 1000 and each unit, and exchanges data, control signals, and the like between them. Reference numeral 1003 denotes a storage device for storing various software, such as a hard disk. Reference numeral 1004 denotes a storage device for accumulating moving image data, and includes, for example, a hard disk and an MO. A display unit 1005 is used to display images, messages, and the like. The communication interface 1007 transmits and receives data via the communication circuit 1008, and is connected to a LAN, public line, wireless line, broadcast wave, etc. outside the apparatus. An operation unit 1006 is used to activate the image processing apparatus and set various conditions.

  The memory 1001 stores an OS and software for controlling the operation of the entire image processing apparatus and operating various software, an area for reading image data, a working area for storing various calculation parameters, and the like. Exists.

  In such a configuration, prior to processing, moving image data to be encoded is selected from the moving image data stored in the storage device 1004 from the operation unit 1006, and the activation of the computer is instructed. Then, the software stored in the storage device 1003 is expanded in the memory 1001 via the bus 1002, and the software is activated. Then, in the encoding operation of the moving image data stored in the storage device 1004 by the CPU 1000, the program code (the above-mentioned software) according to the flowcharts shown in FIGS. 5 to 8 is executed.

  As described above, the computer according to the present embodiment functions as a device that realizes noise removal according to the above-described embodiment.

  As described above, according to the present embodiment, in the moving picture coding apparatus and method, it is possible to accurately detect a portion where coding noise such as mosquito noise included in image data is generated. Then, the texture of the original image can be retained, and noise removal processing can be performed only on the noise generation portion.

  Although the embodiments of the present invention have been described in detail above, the present invention may be applied to a system constituted by a plurality of devices or may be applied to an apparatus constituted by one device.

  In the present embodiment, the DCT transform has been described. However, the present invention is not limited to this, and an orthogonal transform that separates into a high frequency and a low frequency, for example, another orthogonal transform such as Hadamard transform or Fourier transform, and quantization are combined. Similar effects can be obtained by encoding.

  In the present embodiment, the encoding method for performing inter-frame encoding such as MPEG has been described as an example, but the present invention is not limited to this. For example, you may adapt to the encoding system coded continuously, such as Motion JPEG encoding system. In the Mption JPEG encoding method, encoding can be performed for each of RGB, and the target signal is not limited to the luminance signal.

  In the present embodiment, the processing in units of frames has been described. However, the present invention is not limited to this. For interlaced images, processing in units of fields may be used.

  In the present invention, a software program that realizes the functions of the above-described embodiments is directly or remotely supplied to a system or apparatus, and the computer of the system or apparatus reads and executes the supplied program. Can also be achieved. In that case, the form does not have to be a program as long as it has the function of the program.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. That is, the claims of the present invention include the computer program itself for realizing the functional processing of the present invention. In this case, the program may be in any form as long as it has a program function, such as an object code, a program executed by an interpreter, or script data supplied to the OS.

  Various storage media for supplying the program can be used. For example, floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card, ROM, DVD (DVD-ROM, DVD- R).

  As another program supply method, the program can be supplied by connecting to a homepage on the Internet using a browser of a client computer and downloading the program from the homepage to a storage medium such as a hard disk. In this case, the computer program itself of the present invention or a compressed file including an automatic installation function may be downloaded. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the claims of the present invention.

  Further, the program of the present invention may be encrypted, stored in a storage medium such as a CD-ROM, and distributed to users. In that case, a user who has cleared a predetermined condition is allowed to download key information to be decrypted from a homepage via the Internet, and using the key information, the encrypted program can be executed on a computer in a format that can be executed. To be installed.

  Further, the present invention can be realized in a form other than the form in which the functions of the above-described embodiments are realized by the computer executing the read program. For example, based on the instructions of the program, an OS or the like running on the computer performs part or all of the actual processing, and the functions of the above-described embodiments can also be realized by the processing.

  Furthermore, the program read from the storage medium may be written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer. In this case, thereafter, based on the instructions of the program, the CPU or the like provided in the function expansion board or function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing. .

It is a block diagram which shows the structure of the principal part of the image processing apparatus which concerns on embodiment of this invention. It is a figure which shows an example of the operator of the Sobel filter used by this embodiment. It is a figure which shows the example of a relationship between an edge strength change value and a filter strength multiplier. It is a figure which shows an example of the epsilon filter concerning this embodiment. It is a flowchart explaining the process with respect to the top frame of the image processing apparatus which concerns on Embodiment 1 of this invention. 4 is a flowchart for explaining processing of frames after the first frame of the image processing apparatus according to the first embodiment of the present invention. It is a flowchart explaining the generation method of the noise removal flag map which concerns on this embodiment. It is a flowchart explaining the strength calculation method of the filter concerning this embodiment. It is a figure explaining the example (B) of extending the edge area | region of the specific flame | frame immediately before, and determining the noise removal object block of the present flame | frame. It is a block diagram explaining the hardware constitutions of the image processing apparatus which concerns on this embodiment.

DESCRIPTION OF SYMBOLS 100 Horizontal edge strength measuring device 101 Vertical edge strength measuring device 102 Edge strength memory 103 Noise removal flag calculator 104 Noise removal flag memory 105 Filter strength multiplier table 106 Filter strength calculator 107 Filter

Claims (9)

An image processing apparatus for removing noise components of decoded image data obtained by decoding an image stream generated by lossy encoding,
Horizontal edge strength measuring means for measuring the strength of the horizontal edge of each block of the input frame;
Vertical edge strength measuring means for measuring the strength of the vertical edge of each block of the input frame;
Edge strength storage means for storing horizontal and vertical edge strengths measured by the horizontal edge strength measurement means and the vertical edge strength measurement means;
Noise removal flag calculation means for calculating a noise removal flag for identifying a block from which noise should be removed based on the horizontal and vertical edge strengths stored in the edge strength storage means;
Noise removal flag storage means for storing the noise removal flag calculated by the noise removal flag calculation means;
Filter control means for outputting a control signal for controlling a filter for performing noise removal based on the input edge strength of the current frame, the edge strength of the immediately preceding frame stored in the edge strength storage means, and the noise removal flag;
Have a filtering means for performing filtering processing on the current frame in response to the control signal from the filter control means,
The filter control means includes
The edge strength of the block of the current frame measured by the horizontal edge strength measurement means and the vertical edge strength measurement means, and the edge of the block corresponding to the block of the current frame of the immediately preceding frame stored in the edge strength storage means An image processing apparatus that calculates a filter strength based on a product of a difference from the strength and a strength multiplier of the filter strength and outputs the control signal for the block from which the noise is to be removed. . The noise removal flag calculation means includes
Means for obtaining edge strength of each block with reference to the edge strength storage means;
A first block having the acquired edge strength greater than a first predetermined value, and a second block adjacent to the first block and having an edge strength that is smaller than a second predetermined value by an edge strength of the first block. And means for obtaining
The image processing apparatus according to claim 1, wherein the noise removal flag is information specifying the second block. Edge strength of the block, the image processing apparatus according to claim 1 or 2, characterized in that the sum of the horizontal edge intensity and the vertical edge intensity of the block. Further comprising a filter strength multiplier table for storing the intensity multiplier in response to the difference, the filter control unit 1 through claim and acquires the intensity multiplier with reference to the filter strength multiplier table 4. The image processing apparatus according to any one of items 3 . The edge strength storing means has a memory having a bank configuration having at least two banks for storing horizontal and vertical edge strengths for one frame, and stores edge strength in one bank while edge strength is stored from the other bank. the image processing apparatus according to any one of claims 1 to 4, characterized in that the reading has been configured to be. The noise removal flag storage means includes a bank memory having at least two banks for storing noise removal flags for one frame, and stores noise removal flags in one bank while removing noise removal flags from the other bank. the image processing apparatus according to any one of claims 1 to 5, characterized in that the reading has been configured to be. The computer according to any one of claims 1 to 6 , in order to cause the computer to function as an image processing device that removes a noise component of decoded image data obtained by decoding an image stream generated by lossy encoding. A program for functioning as an image processing apparatus. A computer-readable storage medium storing the program according to claim 7 . An image processing method of an image processing apparatus for removing a noise component of decoded image data obtained by decoding an image stream generated by lossy encoding,
A horizontal edge strength measurement process for measuring the strength of the horizontal edge of each block of the input frame;
A vertical edge strength measurement step for measuring the strength of the vertical edge of each block of the input frame;
An edge strength storing step for storing horizontal and vertical edge strengths measured in the horizontal edge strength measuring step and the vertical edge strength measuring step;
A noise removal flag calculation step for calculating a noise removal flag for identifying a block from which noise is to be removed based on the horizontal and vertical edge strengths stored in the edge strength storage step;
A noise removal flag storage step for storing the noise removal flag calculated in the noise removal flag calculation step;
A filter control step for outputting a control signal for controlling a filter for performing noise removal based on the input edge strength of the current frame, the edge strength of the immediately preceding frame stored in the edge strength storage step, and the noise removal flag;
Said have a filter step of performing filtering processing for the current frame in response to said control signal output by the filter control step,
In the filter control step,
The edge strength of the block of the current frame measured in the horizontal edge strength measurement step and the vertical edge strength measurement step, and the edge of the block corresponding to the block of the current frame in the immediately preceding frame stored in the edge strength storage step An image processing apparatus that calculates a filter strength based on a product of a difference from the strength and a strength multiplier of the filter strength and outputs the control signal for the block from which the noise is to be removed. Image processing method.

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