CN113301347A - Optimization method of HEVC high-definition video coding - Google Patents

Optimization method of HEVC high-definition video coding Download PDF

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CN113301347A
CN113301347A CN202110501572.8A CN202110501572A CN113301347A CN 113301347 A CN113301347 A CN 113301347A CN 202110501572 A CN202110501572 A CN 202110501572A CN 113301347 A CN113301347 A CN 113301347A
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CN113301347B (en
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郭雅婷
钟辰威
张泽琦
徐雍
鲁仁全
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Guangdong University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/46—Embedding additional information in the video signal during the compression process
    • H04N19/463—Embedding additional information in the video signal during the compression process by compressing encoding parameters before transmission
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/157—Assigned coding mode, i.e. the coding mode being predefined or preselected to be further used for selection of another element or parameter
    • H04N19/159—Prediction type, e.g. intra-frame, inter-frame or bidirectional frame prediction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/625—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using discrete cosine transform [DCT]

Abstract

An optimization method for HEVC high definition video coding comprises the following steps: dividing an original video image into a plurality of mutually independent coding units, namely original image blocks; performing predictive coding, including removing redundant information and obtaining a predictive image block by adopting intra-frame prediction and inter-frame prediction modes respectively according to the time redundancy and the spatial redundancy of the video image; obtaining a prediction residual based on the difference value of the image values of the prediction block and the original image block, and performing discrete cosine transform and quantization on the prediction residual; entropy coding is carried out on the quantized discrete cosine transform coefficient to obtain a compressed code stream of the video sequence, and the compressed code stream is output; and decoding the compressed code stream to obtain a high-resolution video sequence, and performing image interpolation on the high-resolution video sequence to restore the image size of the high-resolution video sequence to the original image size. The coding scheme with higher coding efficiency, better performance and lower computational complexity is obtained under the condition of little change of video quality, and the method is more favorable for video transmission and storage in the future.

Description

Optimization method of HEVC high-definition video coding
Technical Field
The invention relates to the technical field of video coding, in particular to an optimization method of HEVC high-definition video coding.
Background
High Efficiency Video Coding (HEVC), also known as h.265, can achieve twice as much compression by the blu-ray best video compression method; however, the existing HEVC coding technology has many defects, such as the following defects:
firstly, the complexity of HEVC coding is much higher than other video coding standards, so the performance is not good under the condition of low code rate, and the decoded video has more serious distortion;
secondly, although the compression method based on image downsampling greatly reduces the calculated amount of coding and relieves the pressure on wireless network transmission, the method can be smoother when interpolating a flat area in an image, but the interpolation effect on detailed parts such as the edge and texture of the image is general, and serious fuzzy and sawtooth effects exist, so that the visual effect of the reconstructed image is poor;
third, the transform method adopted in HEVC is implemented by performing two basic one-dimensional transforms in the horizontal and vertical directions separately in the actual coding. However, for two-dimensional images where the dominant direction of the internal texture is not horizontal or vertical, conventional two-dimensional transforms do not compress their energy best. Therefore, neither the DCT nor the DST transform used in HEVC can take into account the detail content of the image very well.
Disclosure of Invention
The invention aims to provide an optimization method of HEVC high-definition video coding aiming at the defects in the background art, so that a coding scheme with higher coding efficiency, better performance and lower computational complexity is obtained under the condition of small video quality change, and the method is more favorable for video transmission and storage in the future.
In order to achieve the purpose, the invention adopts the following technical scheme:
an optimization method for HEVC high definition video coding comprises the following steps:
step A: inputting an original video sequence at an encoding end and performing downsampling to obtain a degraded low-resolution video sequence;
and B: an HEVC encoder encodes a low resolution video sequence, comprising:
each frame of input original video image is divided into a plurality of mutually independent coding units, namely original image blocks;
performing predictive coding, including removing redundant information and obtaining a predictive image block by adopting intra-frame prediction and inter-frame prediction modes respectively according to the time redundancy and the spatial redundancy of the video image;
obtaining a prediction residual based on the difference value of the image values of the prediction block and the original image block, and performing discrete cosine transform and quantization on the prediction residual;
entropy coding is carried out on the quantized discrete cosine transform coefficient to obtain a compressed code stream of the video sequence, and the compressed code stream is output;
and C: and the decoder decodes the compressed code stream to obtain a high-resolution video sequence, and performs image interpolation on the high-resolution video sequence to restore the image size of the high-resolution video sequence to the original image size.
Preferably, in the step B, selecting a PU prediction mode with a minimum rate-distortion cost value at a maximum probability of a current frame coding unit according to a size relationship between the current frame coding unit and a corresponding frame coding unit, specifically includes:
when the side length of the current frame coding unit is smaller than the side length of the corresponding frame coding unit, the method comprises the following steps:
when the side length of the current frame coding unit is half of the side length of the corresponding frame coding unit, if the PU prediction mode of the partition of the corresponding frame coding unit is nL multiplied by 2N, the PU prediction mode of the partition of the current frame coding unit is selected to be Nmultiplied by 2N; if the PU prediction mode of the partition corresponding to the frame coding unit is 2 NxnU; selecting the PU prediction mode of the block of the current frame coding unit as 2 NxN;
when the side length of the current frame coding unit is one fourth of the side length of the corresponding frame coding unit, selecting a PU (polyurethane) prediction mode of a block of the current frame coding unit to be 2 Nx 2N;
when the side length of the current frame coding unit is less than one fourth of the side length of the corresponding frame coding unit, the partition of the current frame coding unit does not select the PU prediction mode.
Preferably, when the side length of the current frame coding unit is greater than the side length of the corresponding frame coding unit, the judgment is carried out according to the size of each block of the corresponding frame coding unit and the PU prediction mode, and the PU prediction module is selected according to the distribution condition of the blocks of the corresponding frame coding unit and the prediction units thereof;
and when the side length of the current frame coding unit is equal to the side length of the corresponding frame coding unit, the coding unit of the current frame selects the PU prediction mode which is the same as the partition of the corresponding frame coding unit.
Preferably, in the step B, the discrete cosine transforming and quantizing the prediction residual includes:
the method comprises the steps of establishing intra-frame prediction models in different modes according to the HEVC standard, obtaining an initial pixel covariance matrix according to a direction-based rotation ellipse model, updating a residual pixel expression according to the initial pixel covariance matrix to obtain a residual pixel covariance matrix, decomposing and adjusting the residual pixel covariance matrix through KLT, and extracting a transformation matrix.
Preferably, the obtaining the initial pixel covariance matrix according to the direction-based ellipse model comprises:
a rotation ellipse model based on the image texture direction is established,
obtaining an offset angle corresponding to a PU prediction mode of a current frame coding unit, namely an image texture direction corresponding to the rotation ellipse model;
obtaining the correlation between pixel points A (a, B) and B (c, d) in a current frame coding unit, wherein the correlation is as follows:
Figure BDA0003056634730000031
wherein:
r represents the ratio of the major and minor axes;
theta represents the direction of texture in the current frame coding unit, namely an angle value;
ρ represents the correlation strength between pixels;
d1(θ)，d2(theta) represents the projection coordinates of the pixel points A and B in the rotating ellipse model;
the mapping relation between the projection coordinates and the real coordinates A (a, B) and B (c, d) is as follows:
Figure BDA0003056634730000041
and sleeving the pixel value of the current frame coding unit and the reference pixel value of the boundary of the adjacent coding unit into the rotation ellipse model, acquiring the correlation between the current frame coding unit and the adjacent coding unit thereof, and acquiring an initial pixel covariance matrix.
Preferably, the establishing of the intra prediction model includes:
and mapping the reference pixel: mapping all reference pixels required by a current frame coding unit into a row or a column;
obtaining a predicted pixel value P according toi，j：
Pi，j＝((32-ω)×Mon0，pla+ω×Mon0，pla+1+16)；
Figure BDA0003056634730000042
Wherein:
omega represents the weight of interpolation operation;
Mon0，plaand Mon0，pla+1Representing a reference pixel mapped by the current prediction pixel;
pla represents the corresponding reference pixel location;
offset [ P ] represents the offset corresponding to the current mode;
(x, y) represents the coordinates of the current predicted pixel.
Preferably, obtaining the residual pixel covariance matrix comprises:
for a residual pixel block with a size of N × N and selected intra-frame prediction mode in intra-frame coding, transposing the residual pixel block into a one-dimensional vector form
Figure BDA0003056634730000051
With a covariance matrix of R (size N)2×N2)：
Figure BDA0003056634730000052
Wherein each element Ra，bComprises the following steps:
Rb，a＝Ra，b＝E{ea，eb}，a，b＝1，2，…，N2；
extracting the transformation matrix includes:
solving an initial KLT transformation matrix based on the residual pixel covariance matrix, and adjusting the amplification factor and the scanning sequence of an integer matrix in transformation coding of the initial KLT transformation matrix;
for coding units whose scanning order is horizontal scanning, the magnification and scanning order of the integer matrix of transform coding are not adjusted;
for coding units with vertical scanning sequence, arranging the characteristic vectors in the initial KLT transformation matrix according to the sequence consistent with the energy arrangement in the HEVC standard;
for coding units with a scanning sequence of diagonal scanning, arranging the initial KLT transformation matrixes according to the same energy sequence in the HEVC standard;
preferably, in step C, the method includes interpolating the low-resolution video image to be restored by using the intra-frame redundant similarity structure to obtain the high-resolution prediction image block, and specifically includes:
expanding a search area by utilizing similarity, and increasing the number of image blocks which can be referred to, the method comprises the following specific steps:
selecting an original image block Pi to be interpolated in a video image of a current frame as a target center, and establishing a window with radius r in the current video image;
determining a search frame with the same position and size as a window in each L frame of video images before and after the video image of the current frame, and using the search frame as a search area of a similar neighbor block of an original image block Pi;
respectively putting the image blocks in the search area into a down-sampling grid, and sequentially calculating the similarity between the image blocks and the original image blocks Pi;
selecting the most similar N image blocks to fit the original image blocks Pi to obtain image blocks similar to the original image blocks Pi, and marking the similar image blocks respectively;
down-sampling the marked image blocks again and splicing the marked image blocks into high-resolution prediction image blocks;
and continuously and iteratively updating the prediction image block to ensure that the approximation degree of the prediction image block and the original image block to be interpolated reaches the highest.
Preferably, the determining the similarity between the image block of the search area and the original image block includes:
acquiring a difference value of the alignment gray value of an original image block to be interpolated and each image block in a search area;
accumulating and summing the absolute values of the difference values;
and selecting the image blocks corresponding to the first K minimum numerical values to linearly represent the original image blocks to be interpolated, wherein the image blocks corresponding to the first K minimum numerical values have the highest similarity with the original image blocks to be interpolated.
Preferably, in the step C, the method further includes reducing the radius of the search box and reducing the number of iterations, so as to improve the similarity between the prediction image block and the original image block to be interpolated.
Compared with the prior art, the invention has the following beneficial effects:
firstly, in the aspect of intra-frame prediction, the video image is firstly downsampled by utilizing the similarity prior information between the images, then compression coding is carried out, and image interpolation is carried out on the video data after decoding so as to restore the video data to the original resolution. The method expands the search area of the image block to be interpolated in the current video frame to the adjacent multi-frame video image, expands the search area, increases the number of the image blocks which can be referred to, has stronger fitting capability and clearer synthetic image; meanwhile, the data size of the code can be greatly reduced, and higher video quality can be output under the condition of low code rate;
secondly, in the aspect of inter-frame prediction, the temporal correlation between the CU partition mode and the PU prediction mode between adjacent frames is utilized to skip some CU partition modes and PU prediction modes of the current block in a targeted manner, and then the difference value is calculated and transmitted. This has the advantage of being simpler and more efficient than all previous methods for computing retransmissions, thereby reducing the coding computational complexity of HEVC.
Thirdly, in the aspect of transformation, a rotation ellipse model considering the directional information of the image is established, and a series of improved transformation methods are designed based on the principle of KLT transformation. Then, different transformation methods with fixed forms are respectively extracted according to different intra-frame prediction modes, and the different transformation methods are correspondingly put into the HEVC standard to replace the original transformation and then applied.
Drawings
Fig. 1 is an HEVC encoding flow diagram of one embodiment of this disclosure;
FIG. 2 is a diagram illustrating the prediction modes of nL × 2N PU according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a PU prediction mode of 2 NxnU according to an embodiment of the present invention;
FIG. 4 is a diagram of PU prediction modes in the prior art;
FIG. 5 is a flow diagram of an improved transformation module of one embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of illustrating the present invention and are not to be construed as limiting the present invention;
any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
The invention provides an optimization method of HEVC high-definition video coding, which comprises the steps of adopting a video image interpolation scheme based on self-similarity, an inter-frame mode quick selection mode based on time domain correlation and a high-definition video coding scheme based on a transformation method of a rotation ellipse model and KLT (Kelvin transform);
the method comprises the steps of firstly carrying out down-sampling processing on an original video sequence at a coding end so as to obtain a reduced low-resolution small video, and then coding the small video by using an HEVC coder. Secondly, a method for quickly selecting an inter-frame mode based on time domain correlation is established, and a prediction mode is quickly determined according to the side length of a coding unit of a current frame. Finally, a rotation ellipse model considering the directional information of the image is established, transformation methods under different prediction modes are designed based on the KLT transformation principle, the transformation methods are correspondingly put into the HEVC standard to replace the original transformation and then tested, the transmission is carried out after the coding is finished, and finally, a decoder carries out image interpolation on the decoded small video to restore the size of the initial image;
the method specifically comprises the following steps:
step A: inputting an original video sequence at an encoding end and performing downsampling to obtain a degraded low-resolution video sequence;
and B: an HEVC encoder encodes a low resolution video sequence, comprising:
each frame of input original video image is divided into a plurality of mutually independent coding units, namely original image blocks;
performing predictive coding, including removing redundant information and obtaining a predictive image block by adopting intra-frame prediction and inter-frame prediction modes respectively according to the time redundancy and the spatial redundancy of the video image;
obtaining a prediction residual based on the difference value of the image values of the prediction block and the original image block, and performing discrete cosine transform and quantization on the prediction residual;
entropy coding is carried out on the quantized discrete cosine transform coefficient to obtain a compressed code stream of the video sequence, and the compressed code stream is output;
and C: and the decoder decodes the compressed code stream to obtain a high-resolution video sequence, and performs image interpolation on the high-resolution video sequence to restore the image size of the high-resolution video sequence to the original image size.
The inter prediction modes include: 2 nx 2N, N xn, 2 nx N, N X2N, nL X2N, nR X2N, 2 nxnu and 2 nxnd, as shown in fig. 4, each mode is divided in a format of (width [2 nx ] height [2N ]), and when each coding unit is divided into upper, lower, and upper large blocks, the height [2N ] may be expressed as nU and N U's equal to 2N, and similarly, when each coding unit is divided into left, lower, and right large blocks, the width [2N ] may be expressed as nL and N's equal to 2N;
in this embodiment, regarding that the PU prediction mode for selecting the minimum rate-distortion cost value of the maximum probability of the current frame coding unit is a fast inter-frame mode selection mode based on the temporal correlation, the PU mode with the highest probability of occurrence in inter-frame prediction is found out according to the distribution of different PUs under various sizes of CUs by first counting and comprehensively analyzing the temporal correlation between the corresponding frame Coding Unit (CU) and Prediction Unit (PU) between frames. The method skips some high-similarity CU partition layers and PU prediction modes, and the CU layers only take two PU prediction modes at most, thereby greatly reducing the number of rate-distortion cost calculation required. With little loss in bit rate and video quality, nearly half of the encoding time can be saved. Then, according to the size relationship between the current frame coding unit and the corresponding frame coding unit, three cases are divided for discussion, each type respectively uses a set method to calculate the PU prediction mode of the current image block with the maximum probability of the minimum rate-distortion cost value according to the prediction mode of the prediction unit, and lists the inter-frame mode methods under 3 cases according to the statistical result, which is specifically as follows:
when the side length of the current frame coding unit is smaller than the side length of the corresponding frame coding unit, the method comprises the following steps:
when the side length of the current frame coding unit is half of the side length of the corresponding frame coding unit, if the PU prediction mode of the partition of the corresponding frame coding unit is nL multiplied by 2N, the PU prediction mode of the partition of the current frame coding unit is selected to be Nmultiplied by 2N; if the PU prediction mode of the partition corresponding to the frame coding unit is 2 NxnU; selecting the PU prediction mode of the block of the current frame coding unit as 2 NxN;
as shown in fig. 2, when the side length of the current CU is half of the corresponding block, the block P may correspond to a position of C, D, E or F. When the PU mode of the block corresponding to the previous frame is nL multiplied by 2N, selecting Nmultiplied by 2N for the PU mode of the CU block of the current frame; as shown in fig. 3, if the PU mode is 2N × nU, then 2N × N is selected as the PU mode of the current CU block;
when the side length of the current frame coding unit is one fourth of the side length of the corresponding frame coding unit, selecting a PU (polyurethane) prediction mode of a block of the current frame coding unit to be 2 Nx 2N;
when the side length of the current frame coding unit is less than one fourth of the side length of the corresponding frame coding unit, the partition of the current frame coding unit does not select the PU prediction mode.
Preferably, when the side length of the current frame coding unit is greater than the side length of the corresponding frame coding unit, the judgment is carried out according to the size of each block of the corresponding frame coding unit and the PU prediction mode, and the PU prediction module is selected according to the distribution condition of the blocks of the corresponding frame coding unit and the prediction units thereof;
in addition to the mode 2N × 2N, other modes must be determined by the size of each CU partition in the corresponding block and the PU prediction mode. Through a large number of experimental statistics, 6 modes (2N × 2N, 2N × N, N × 2N, nL × 2N, nR × 2N, 2N × nU and 2N × nD) are divided into 2 types, namely vertical and horizontal, and which prediction mode is selected is determined according to the distribution of specific coding units and prediction units in a corresponding block.
And when the side length of the current frame coding unit is equal to the side length of the corresponding frame coding unit, the coding unit of the current frame selects the PU prediction mode which is the same as the partition of the corresponding frame coding unit.
The optimized transformation scheme based on different intra and inter prediction modes in this embodiment is specifically as follows:
as shown in fig. 5, intra-frame prediction models in different modes are first established according to the HEVC standard, then a residual pixel expression is updated by using a pixel covariance matrix obtained by an ellipse model based on a direction, then a residual pixel covariance matrix is obtained, and then a transformation matrix is extracted through KLT decomposition and adjustment. The improved transform method may improve the overall coding efficiency on the luminance component and the chrominance component.
Preferably, in the step B, the discrete cosine transforming and quantizing the prediction residual includes:
the method comprises the steps of establishing intra-frame prediction models in different modes according to the HEVC standard, obtaining an initial pixel covariance matrix according to a direction-based rotation ellipse model, updating a residual pixel expression according to the initial pixel covariance matrix to obtain a residual pixel covariance matrix, decomposing and adjusting the residual pixel covariance matrix through KLT, and extracting a transformation matrix.
And establishing an elliptical model based on the texture direction information to obtain a covariance matrix of the initial pixel. After the image frame is subjected to the blocking operation, the encoding unit has a dominant direction. The traditional circular model ignores that the pixel points in the dominant direction are more relevant than the rest. In order to fully utilize the original directional information of the image and improve the accuracy of prediction.
Preferably, the obtaining the initial pixel covariance matrix according to the direction-based ellipse model comprises:
a rotation ellipse model based on the image texture direction is established,
obtaining an offset angle corresponding to a PU prediction mode of a current frame coding unit, namely an image texture direction corresponding to the rotation ellipse model;
obtaining the correlation between pixel points A (a, B) and B (c, d) in a current frame coding unit, wherein the correlation is as follows:
Figure BDA0003056634730000121
wherein:
r represents the ratio of the major and minor axes;
theta represents the direction of texture in the current frame coding unit, namely an angle value;
ρ represents the correlation strength between pixels;
d1(θ)，d2(theta) represents the projection coordinates of the pixel points A and B in the rotating ellipse model;
the mapping relation between the projection coordinates and the real coordinates A (a, B) and B (c, d) is as follows:
Figure BDA0003056634730000122
and sleeving the pixel value of the current frame coding unit and the reference pixel value of the boundary of the adjacent coding unit into the rotation ellipse model, acquiring the correlation between the current frame coding unit and the adjacent coding unit thereof, and acquiring an initial pixel covariance matrix.
Preferably, the establishing of the intra prediction model includes:
and mapping the reference pixel: mapping all reference pixels required by a current frame coding unit into a row or a column;
obtaining a predicted pixel value P according toi，j：
Pi，j＝((32-ω)×Mon0，pla+ω×M0n0，pla+1+16)；
Figure BDA0003056634730000123
Wherein:
omega represents the weight of interpolation operation;
Mon0，plaand Mon0，pla+1Representing a reference pixel mapped by the current prediction pixel;
pla represents the corresponding reference pixel location;
offset [ P ] represents the offset corresponding to the current mode;
(x, y) represents the coordinates of the current predicted pixel.
And establishing an intra-frame prediction model. According to the HEVC standard, intra prediction pixels are calculated differently in different modes. Firstly, mapping processing is carried out on reference pixels: in the intra prediction of HEVC, all reference pixels needed by the current block are mapped into a line (denoted as Mon) or a column according to the prediction mode, and the pixel values in the subsequent TU are derived from the reconstructed reference pixels. And then, calculating a predicted pixel value, wherein after the one-dimensional reference pixel set corresponding to the mode is obtained, each predicted pixel value is obtained by performing one-time interpolation operation on two reference pixels corresponding to the coordinates.
When the corresponding offset value is 0 or 32 and the corresponding ω is 0, each pixel of the current block is only related to one reference pixel in the interpolation operation of the prediction value in the mode. Otherwise, the pixel point is related to two reference pixel points;
a covariance matrix of the residuals is calculated. The operation object of the transformation is residual data, and in order to obtain the improved transformation matrix, the covariance matrix of the residual block in different prediction modes must be calculated. The value of the prediction residual is equal to the difference between the true value of the current pixel and its predicted value. Firstly, according to any two residual pixels in the predicted residual pixel block
Figure BDA0003056634730000131
Obtaining the correlation size of the two, combining the coordinates of the two residual pixels in the current transformation unit and the position of the reference pixel, and combining the initial pixel set and the reference pixelAnd (4) solving the correlation between two predicted residual pixels by the relationship between every two pixel sets.
Preferably, obtaining the residual pixel covariance matrix comprises:
for a residual pixel block with a size of N × N and selected intra-frame prediction mode in intra-frame coding, transposing the residual pixel block into a one-dimensional vector form
Figure BDA0003056634730000132
With a covariance matrix of R (size N)2×N2)：
Figure BDA0003056634730000133
Wherein each element Ra，bComprises the following steps:
Rb，a＝Ra，b＝E{ea，eb}，a，b＝1，2，…，N2；
extracting the transformation matrix includes:
solving an initial KLT transformation matrix based on the residual pixel covariance matrix, and adjusting the amplification factor and the scanning sequence of an integer matrix in transformation coding of the initial KLT transformation matrix;
an improved transformation matrix is solved. The KLT transform has transform performance that cannot be achieved by other transform methods, and in order to apply the transform matrix of the method to the actual HEVC coding standard, the transform matrix needs to be adjusted by referring to the integer transform method in HEVC, one is to adjust the magnification to keep the transform coding precision unchanged and the scanning order to keep the energy distribution unchanged, and the two operations are not in sequence. Firstly, solving a covariance matrix of a residual error pixel block under any intra-frame prediction mode by combining a rotation ellipse model and an intra-frame prediction model, and then solving an initial KLT transformation matrix; adjusting the initial KLT matrix results in an improved transform matrix.
The initially decomposed transformation matrix is sequentially arranged in a descending order from top to bottom according to the eigenvectors corresponding to the eigenvalues. To obtain the KLT transform matrix, a decomposition of the eigenvalues of the standard is required. Intra prediction for a NxN size selectionResidual pixel blocks of pattern P. Similar to the amplification factor of integer matrix in transform coding in HEVC standard, for a transform unit with size N × N, the corresponding transform matrix needs to be amplified when performing integer operation
Figure BDA0003056634730000141
And (4) doubling. In order to keep the order of the improved transformed transform coefficients and the transform coding in HEVC unchanged and keep the frame of the transform in HEVC basically unchanged, the transform method proposed in this patent is inseparable and therefore can be derived with only one multiplication. The improved transform matrix needs to be scaled up 4096N times on the basis of the initial KLT decomposition matrix and then rounded up.
Since the initial KLT transform matrix obtained by this patent is not suitable for other prediction modes using vertical scan order or diagonal scan order. Therefore, we need to make corresponding adjustment to the transform matrix based on the intra prediction mode corresponding to the current coefficient block:
for image blocks with a prediction mode of 22-30, a scanning sequence adopted in HEVC is horizontal scanning, and in order to keep the coefficient energy distribution consistent with the arrangement of an initial KLT matrix, the improved transform coding does not need to be adjusted;
for image blocks with prediction modes of 6-14, a vertical scanning sequence is adopted on an HEVC frame, and at the moment, an improved transformation method needs to put feature vectors in a KLT matrix in a sequence consistent with energy arrangement in HEVC.
For the image blocks of the remaining prediction modes. The adjustment of the transformation matrix is arranged according to the same energy sequence by adopting a diagonal scanning method.
The transformation matrix in the project is replaced and applied. Once the transform unit TU and the prediction mode in intra-frame predictive coding are determined, the covariance matrix is obtained, the eigenvalue decomposition is performed on the covariance matrix, and the eigenvalue decomposition is adjusted according to the property of the transform matrix in the HEVC standard and the rule of transform coefficient entropy coding, so that the improved transform matrix can be obtained. Due to the limitation of the size of the transformation matrix, only residual transformation with the sizes of 4 × 4 and 8 × 8 of the intra-frame coding part in HEVC is changed, namely, the original DCT transformation in the HEVC standard is replaced by improved transformation kernel matrixes with the sizes of 16 × 16 and 64 × 64, each block obtains a corresponding transformation matrix, and then the series of transformation matrixes are numbered and put into engineering, and the transformation matrixes are selected and replaced according to the size of TU (transformation unit) and the prediction mode.
The video is a set of a static image, and usually, the chrominance information of pixel points at the same position in adjacent images is basically unchanged, so that the NPCI algorithm can be widened to the interpolation of the video image, namely, the low-resolution video image to be restored is interpolated by utilizing the similarity structure of the inter-frame redundancy and intra-frame redundancy of the video.
Preferably, in step C, the method includes interpolating the low-resolution video image to be restored by using the intra-frame redundant similarity structure to obtain the high-resolution prediction image block, and specifically includes:
expanding a search area by utilizing similarity, and increasing the number of image blocks which can be referred to, the method comprises the following specific steps:
selecting an original image block Pi to be interpolated in a video image of a current frame as a target center, and establishing a window with radius r in the current video image;
determining a search frame with the same position and size as a window in each L frame of video images before and after the video image of the current frame, and using the search frame as a search area of a similar neighbor block of an original image block Pi;
respectively putting the image blocks in the search area into a down-sampling grid, and sequentially calculating the similarity between the image blocks and the original image blocks Pi;
selecting the most similar N image blocks to fit the original image blocks Pi to obtain image blocks similar to the original image blocks Pi, and marking the similar image blocks respectively;
down-sampling the marked image blocks again and splicing the marked image blocks into high-resolution prediction image blocks;
and continuously and iteratively updating the prediction image block to ensure that the approximation degree of the prediction image block and the original image block to be interpolated reaches the highest.
The image block that is continuously updated will be closer to the image block to be interpolated. However, the number of iterations is not too large, so that overfitting is easy to occur, and the calculation amount is too large.
Preferably, the determining the similarity between the image block of the search area and the original image block includes:
acquiring a difference value of the alignment gray value of an original image block to be interpolated and each image block in a search area;
accumulating and summing the absolute values of the difference values;
and selecting the image blocks corresponding to the first K minimum numerical values to linearly represent the original image blocks to be interpolated, wherein the image blocks corresponding to the first K minimum numerical values have the highest similarity with the original image blocks to be interpolated.
Preferably, in the step C, the method further includes reducing the radius of the search box and reducing the number of iterations, so as to improve the similarity between the prediction image block and the original image block to be interpolated.
The radius of a search window and the iteration times are reduced to prevent the quality of the interpolation image from being reduced, and meanwhile, the running speed is higher. The search window is mainly used for searching non-local similar neighbor blocks, so the larger the window is, the more similar blocks are searched, and the more accurate the image restored finally. However, an excessively large window increases the amount of unnecessary computation, and degrades the performance of interpolation. The choice of the value of K directly affects the quality of the interpolated image. Images with different characteristics preferably have different K values.
Although the numerical value difference between the values of the parameters (such as the size of a search window of an adjacent area and the size of an image block) is small, the calculation amount of the algorithm is greatly increased, so that an appropriate value needs to be set according to a specific scene;
the technical principle of the present invention is described above in connection with specific embodiments. The description is made for the purpose of illustrating the principles of the invention and should not be construed in any way as limiting the scope of the invention. Based on the explanations herein, those skilled in the art will be able to conceive of other embodiments of the present invention without inventive effort, which would fall within the scope of the present invention.

Claims (10)

1. An optimization method for HEVC high definition video coding is characterized by comprising the following steps: the method comprises the following steps:
step A: inputting an original video sequence at an encoding end and performing downsampling to obtain a degraded low-resolution video sequence;
and B: an HEVC encoder encodes a low resolution video sequence, comprising:
dividing each frame of input original video image into a plurality of mutually independent coding units, namely original image blocks;
performing predictive coding, including removing redundant information and obtaining a predictive image block by adopting intra-frame prediction and inter-frame prediction modes respectively according to the time redundancy and the spatial redundancy of the video image;
obtaining a prediction residual based on the difference value of the image values of the prediction block and the original image block, and performing discrete cosine transform and quantization on the prediction residual;
entropy coding is carried out on the quantized discrete cosine transform coefficient to obtain a compressed code stream of the video sequence, and the compressed code stream is output;
and C: and the decoder decodes the compressed code stream to obtain a high-resolution video sequence, and performs image interpolation on the high-resolution video sequence to restore the image size of the high-resolution video sequence to the original image size.
2. The method of claim 1, wherein the HEVC high-definition video coding optimization method comprises the following steps:
in step B, selecting a PU prediction mode with the minimum rate-distortion cost value at the maximum probability of the current frame coding unit according to the size relationship between the current frame coding unit and the corresponding frame coding unit, specifically including:
when the side length of the current frame coding unit is smaller than the side length of the corresponding frame coding unit, the method comprises the following steps:
when the side length of the current frame coding unit is half of the side length of the corresponding frame coding unit, if the PU prediction mode of the partition of the corresponding frame coding unit is nL multiplied by 2N, the PU prediction mode of the partition of the current frame coding unit is selected to be Nmultiplied by 2N; if the PU prediction mode of the partition corresponding to the frame coding unit is 2 NxnU; selecting the PU prediction mode of the block of the current frame coding unit as 2 NxN;
when the side length of the current frame coding unit is one fourth of the side length of the corresponding frame coding unit, selecting a PU (polyurethane) prediction mode of a block of the current frame coding unit to be 2 Nx 2N;
when the side length of the current frame coding unit is less than one fourth of the side length of the corresponding frame coding unit, the partition of the current frame coding unit does not select the PU prediction mode.
3. The method of claim 2, wherein the HEVC high-definition video coding optimization method comprises the following steps:
when the side length of the current frame coding unit is larger than that of the corresponding frame coding unit, judging according to the size of each block of the corresponding frame coding unit and a PU prediction mode, and selecting a PU prediction module according to the distribution condition of the blocks of the corresponding frame coding unit and the prediction units thereof;
and when the side length of the current frame coding unit is equal to the side length of the corresponding frame coding unit, the coding unit of the current frame selects the PU prediction mode which is the same as the partition of the corresponding frame coding unit.
4. The method of claim 1, wherein the HEVC high-definition video coding optimization method comprises the following steps:
in step B, the discrete cosine transforming and quantizing the prediction residual includes:
the method comprises the steps of establishing intra-frame prediction models in different modes according to the HEVC standard, obtaining an initial pixel covariance matrix according to a direction-based rotation ellipse model, updating a residual pixel expression according to the initial pixel covariance matrix to obtain a residual pixel covariance matrix, decomposing and adjusting the residual pixel covariance matrix through KLT, and extracting a transformation matrix.
5. The method of claim 4, wherein the HEVC high-definition video coding optimization method comprises the following steps:
obtaining an initial pixel covariance matrix from the orientation-based ellipse model comprises:
a rotation ellipse model based on the image texture direction is established,
obtaining an offset angle corresponding to a PU prediction mode of a current frame coding unit, namely an image texture direction corresponding to the rotation ellipse model;
obtaining the correlation between pixel points A (a, B) and B (c, d) in a current frame coding unit, wherein the correlation is as follows:
Figure FDA0003056634720000031
wherein:
r represents the ratio of the major and minor axes;
theta represents the direction of texture in the current frame coding unit, namely an angle value;
ρ represents the correlation strength between pixels;
d1(θ)，d2(theta) represents the projection coordinates of the pixel points A and B in the rotating ellipse model;
the mapping relation between the projection coordinates and the real coordinates A (a, B) and B (c, d) is as follows:
Figure FDA0003056634720000032
and sleeving the pixel value of the current frame coding unit and the reference pixel value of the boundary of the adjacent coding unit into the rotation ellipse model, acquiring the correlation between the current frame coding unit and the adjacent coding unit thereof, and acquiring an initial pixel covariance matrix.
6. The method of claim 4, wherein the HEVC high-definition video coding optimization method comprises the following steps:
the establishing of the intra-frame prediction model comprises the following steps:
and mapping the reference pixel: mapping all reference pixels required by a current frame coding unit into a row or a column;
obtaining a predicted pixel value P according toi，j：
Pi，j＝((32-ω)XMon0，pla+ω×Mon0，pla+1+16)；
Figure FDA0003056634720000033
Wherein:
omega represents the weight of interpolation operation;
Mon0，plaand Mon0，pla+1Representing a reference pixel mapped by the current prediction pixel;
pla represents the corresponding reference pixel location;
offset [ P ] represents the offset corresponding to the current mode;
(x, y) represents the coordinates of the current predicted pixel.
7. The method of claim 4, wherein the HEVC high-definition video coding optimization method comprises the following steps:
obtaining a residual pixel covariance matrix comprises:
for a residual pixel block with a size of N × N and selected intra-frame prediction mode in intra-frame coding, transposing the residual pixel block into a one-dimensional vector form
Figure FDA0003056634720000041
With a covariance matrix of R (size N)2×N2)：
Figure FDA0003056634720000042
Wherein each element Ra，bComprises the following steps:
Rb，a＝Ra，b＝E{ea，eb}，a，b＝1，2，…，N2；
extracting the transformation matrix includes:
solving an initial KLT transformation matrix based on the residual pixel covariance matrix, and adjusting the amplification factor and the scanning sequence of an integer matrix in transformation coding of the initial KLT transformation matrix;
for coding units whose scanning order is horizontal scanning, the magnification and scanning order of the integer matrix of transform coding are not adjusted;
for coding units with vertical scanning sequence, arranging the characteristic vectors in the initial KLT transformation matrix according to the sequence consistent with the energy arrangement in the HEVC standard;
for coding units with a diagonal scanning order, the initial KLT transform matrices are arranged in the same energy order as in the HEVC standard.
8. The method of claim 1, wherein the HEVC high-definition video coding optimization method comprises the following steps:
in step C, interpolating the low-resolution video image to be restored by using the intra-frame redundant similarity structure to obtain a high-resolution prediction image block, specifically including:
expanding a search area by utilizing similarity, and increasing the number of image blocks which can be referred to, the method comprises the following specific steps:
selecting an original image block Pi to be interpolated in a video image of a current frame as a target center, and establishing a window with radius r in the current video image;
determining a search frame with the same position and size as a window in each L frame of video images before and after the video image of the current frame, and using the search frame as a search area of a similar neighbor block of an original image block Pi;
respectively putting the image blocks in the search area into a down-sampling grid, and sequentially calculating the similarity between the image blocks and the original image blocks Pi;
selecting the most similar N image blocks to fit the original image blocks Pi to obtain image blocks similar to the original image blocks Pi, and marking the similar image blocks respectively;
down-sampling the marked image blocks again and splicing the marked image blocks into high-resolution prediction image blocks;
and continuously and iteratively updating the prediction image block to ensure that the approximation degree of the prediction image block and the original image block to be interpolated reaches the highest.
9. The method of claim 8, wherein the HEVC high-definition video coding optimization method comprises:
judging the similarity between the image block of the search area and the original image block comprises the following steps:
acquiring a difference value of the alignment gray value of an original image block to be interpolated and each image block in a search area;
accumulating and summing the absolute values of the difference values;
and selecting the image blocks corresponding to the first K minimum numerical values to linearly represent the original image blocks to be interpolated, wherein the image blocks corresponding to the first K minimum numerical values have the highest similarity with the original image blocks to be interpolated.
10. The method of claim 8, wherein the HEVC high-definition video coding optimization method comprises:
in the step C, the radius of the search box is reduced and the number of iterations is reduced, so as to improve the similarity between the predicted image block and the original image block to be interpolated.
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