CN113573055B - Deblocking filtering method and device for picture sequence, electronic equipment and medium - Google Patents
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Abstract
The disclosure discloses a deblocking filtering method, device, electronic equipment and medium for a picture sequence, in particular relates to the technical field of artificial intelligence, and especially relates to the technical field of media cloud in cloud computing. The specific implementation scheme is as follows: determining a category of a current picture in the sequence based on a predetermined threshold; based on the determined category, adjusting a boundary threshold value for deblocking filtering a block boundary between two adjacent blocks in the current picture; and selecting a deblocking filter to be applied to the block boundary based on the boundary threshold.
Description
Technical Field
The disclosure relates to the technical field of artificial intelligence, in particular to the technical field of media cloud in cloud computing, and specifically relates to a deblocking filtering method, device, electronic equipment and medium for a picture sequence.
Background
The high efficiency video coding HEVC (High Efficiency Video Coding) is a new generation video coding compression standard that can save nearly 50% of the code rate at equal sharpness compared to the previous generation h.264/AVC standard. It can be widely used in fields related to video compression, such as live broadcast, on demand, etc. The coding framework of HEVC mainly includes prediction, transformation, quantization, loop filtering, entropy coding, etc. Loop filtering is an important module of the encoder, consisting of deblocking filtering (deblocking) and sample adaptive offset (sample adaptive offset). The reason for introducing deblocking filtering is that coding is performed in units of blocks, and the coding process is performed through processes of transformation, quantization, motion compensation, and the like, and boundaries of each block generate discontinuous data, so that a pseudo boundary or a blocking effect appears subjectively, and subjective feeling is affected. Deblocking filtering is performed on the block boundaries to remove artifacts, thereby preserving the true boundaries. However, the boundary threshold offset used in current deblocking filtering needs to traverse all combinations thereof, regardless of the scene and picture complexity of the application, resulting in a significant amount of computation.
Disclosure of Invention
The disclosure provides a deblocking filtering method, a deblocking filtering device, electronic equipment and a deblocking filtering medium for a picture sequence.
According to an aspect of the present disclosure, there is provided a deblocking filtering method for a sequence of pictures, including:
determining a category of a current picture in the sequence based on a predetermined threshold;
based on the determined category, adjusting a boundary threshold value for deblocking filtering a block boundary between two adjacent blocks in the current picture; and
a deblocking filter to be applied to the block boundary is selected based on the boundary threshold.
According to another aspect of the present disclosure, there is provided a deblocking filtering apparatus for a sequence of pictures, comprising:
the picture category determining module is used for determining the category of the current picture in the sequence based on a preset threshold value;
the adjusting module is used for adjusting a boundary threshold value for deblocking filtering of a block boundary between two adjacent blocks in the current picture based on the determined category; and
a selection module selects a deblocking filter to be applied to the block boundary based on the boundary threshold.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method according to an aspect of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform a method according to an aspect of the present disclosure.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a method according to an aspect of the present disclosure.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a flowchart of a deblocking filtering method for a sequence of pictures according to an embodiment of the present disclosure;
FIG. 2 shows a schematic diagram of a block boundary between two adjacent blocks to which deblocking filtering is applied, according to an embodiment of the present disclosure;
FIG. 3 is a flow chart of deriving boundary filter strengths according to an embodiment of the present disclosure;
FIGS. 4A and 4B illustrate schematic diagrams of discontinuities at block boundaries according to embodiments of the present disclosure;
fig. 5 is a flowchart of a deblocking filtering method for a sequence of pictures according to another embodiment of the present disclosure;
FIGS. 6A, 6B, and 6C are schematic diagrams illustrating the application of different deblocking filter filters according to embodiments of the present disclosure;
FIG. 7 is a schematic diagram of applying deblocking filtering to a current picture, according to an embodiment of the present disclosure;
fig. 8 is a schematic diagram of a deblocking filtering apparatus for a sequence of pictures according to embodiments of the present disclosure; and
FIG. 9 illustrates a schematic block diagram of an example electronic device that may be used to implement embodiments of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a flowchart of a deblocking filtering method 100 for a sequence of pictures, according to an embodiment of the present disclosure.
In step S110, a category of a current picture in the sequence is determined based on a predetermined threshold.
In some embodiments, the categories of pictures may include: a high complexity picture with e.g. a high speed moving object, a medium complexity picture with e.g. a low speed moving object, and a low complexity picture with a substantially constant background area.
In step S120, a boundary threshold for deblocking filtering a block boundary between two neighboring blocks within the current picture is adjusted based on the determined category.
In step S130, a deblocking filter to be applied to the block boundary is selected based on a boundary threshold.
In some embodiments, further, the degree of variation and the degree of flatness between samples located on both sides of the block boundary in two adjacent blocks are calculated, and a deblocking filter to be applied to the block boundary is selected based on the degree of variation and the degree of flatness and a boundary threshold. Depending on the degree of filtering, either a strong filter or a weak filter may be applied. The detailed process of deblocking filter selection will be described below.
The design of HEVC has followed a block-based hybrid video coding framework. First, each picture in an input picture sequence is divided into coding tree units. For a picture with three sample arrays, each coding tree unit consists of one luma sample coding tree block and two corresponding chroma sample coding tree blocks and syntax structures for coding the samples; for monochrome pictures, each coding tree unit consists of a block of sample coding trees and a syntax structure for coding the samples. Then, each coding tree block is subjected to recursive quadtree division to obtain a coding block which is a basic unit of intra/inter coding. Subsequently, the encoded blocks are used as tree roots of the prediction tree and the transform tree, one or more prediction blocks are divided via the indication of the division mode flag, and one or more transform blocks are obtained by the quadtree division. The prediction block is a unit on which the same prediction is performed, and the transform block is a unit on which the same transform is performed.
Fig. 2 shows a schematic diagram of a block boundary between two adjacent blocks to which deblocking filtering is applied, according to an embodiment of the present disclosure. Referring to fig. 2, deblocking filtering of hevc processes block boundaries in 8 x 8 sized blocks of all prediction blocks and transform blocks, where the block boundaries are shown in bold solid lines.
Deblocking filtering decisions in HEVC can be divided into 3 stages:
(1) Deriving a boundary filtering strength;
(2) A filtering switch decision;
(3) A deblocking filter is selected.
First, the boundary filter strength is derived. And preliminarily judging whether filtering and filtering parameters are needed according to the coding parameters of the boundary blocks. The use of different coding parameters (e.g., different prediction modes, different reference pictures, different motion vectors, etc.) for neighboring blocks may cause discontinuities in the sample values at the block boundaries.
Fig. 3 shows a flow chart for deriving the boundary filter strength bS. Where P and Q are 4 x 4 sized blocks on either side of the block boundary.
As shown in fig. 3, if P or Q is located in the encoded block having intra prediction as a prediction mode, i.e., P or Q adopts intra prediction, S360 is entered, and bS is set to 2. Otherwise, S370 is entered when at least one of the following conditions is satisfied, bS is set to 1:
(1) At S320, the block boundary is a transform block boundary, and the transform block where P or Q is located contains one or more non-zero transform coefficient levels;
(2) At S330, P and Q refer to different reference pictures;
(3) In the predictions of S340, P and Q, different numbers of motion vectors MV are used; or alternatively
(4) At S350, the absolute value of the difference (of the horizontal or vertical components) of the motion vectors of P and Q is 4 or more.
When S310 to S350 are not satisfied, the process proceeds to S380, where bS is set to 0.
Next, a filter switch decision is made. Discontinuous boundaries of flat areas of the picture are more easily observed due to the spatial masking effect of the human eye.
Fig. 4A and 4B illustrate schematic diagrams of discontinuities at block boundaries according to embodiments of the present disclosure. As shown in fig. 4A, when the sample values on both sides of the boundary are relatively smooth, but a large difference occurs at the boundary, the human eye vision system can clearly recognize such discontinuity at the boundary. When the sample values on both sides of the boundary show a highly varying trend, such discontinuity is not noticeable as shown in fig. 4B. Therefore, it is necessary to adjust the boundary threshold to compare the degree of variation between samples on both sides of the block boundary with an appropriate boundary threshold to decide whether to perform deblocking filtering.
Specifically, taking a vertical block boundary as an example, a block boundary between two adjacent blocks to which deblocking filtering is applied according to an embodiment of the present disclosure is illustrated, and p (x, y), q (x, y) are sample values on both sides of the block boundary, respectively. Calculating the degree of change between samples on both sides of the block boundary by the following equations (1) to (4), wherein dp 0 Representing the degree of variation, dq, between samples of the first row in a P block 0 Representing the degree of variation, dp, between samples of the first row in a Q block 3 Representing the degree of variation between samples of the fourth row in the P block, and dq 3 Representing the degree of variation between samples of the fourth row in the Q block.
dp 0 ＝|p(2，0)-2p(1，0)+p(0，0)| (1)
dq 0 ＝|q(2，0)-2q(1，0)+q(0，0)| (2)
dp 3 ＝|p(2，3)-2p(1，3)+p(0，3)| (3)
dq 3 ＝|q(2，3)-2q(1，3)+q(0，3)| (4)
Further, the texture degree of the vertical block boundary is calculated by the following equation (5):
C B ＝dp 0 +dq 0 +dp 3 +dq 3 (5)
the larger the texture value of a block boundary region, the more uneven the region, and when the texture value is large to some extent, the deblocking filter switch may be turned off. Thus, a boundary threshold β is set in HEVC, which turns the filter switch of the block boundary on when the following equation (6) is satisfied, and off otherwise:
C B ＜β (6)
by predetermining the class of the picture before deblocking filtering the picture, thereby setting different boundary thresholds for different classes of pictures, the decision accuracy of whether and what deblocking filter is applied to the block boundary can be improved. In addition, different boundary thresholds are set for pictures of different categories based on predetermined picture categories, so that the calculation amount of traversing the combination of various boundary thresholds for each picture can be greatly reduced.
Fig. 5 is a flow chart of a deblocking filtering method 500 for a sequence of pictures according to another embodiment of the present disclosure.
In fig. 5, steps S530 and S540 correspond to steps S120 and S130, respectively, in method 100. Further, prior to step S530, step S110 in method 100 is subdivided into steps S510 and S520.
In step S510, the texture degrees of the plurality of sample pictures are calculated, and a predetermined threshold is set based on the calculated texture degrees.
In some embodiments, the texture degree μ of each sample picture may be calculated by the variance of the gray level histogram of the picture 2 (z)：
Where z is the gray scale of the picture, p (z i ) Is the corresponding histogram, L is the number of different gray levels, and m is the mean of z:
the texture degree calculation is performed on a plurality of sample pictures, wherein the sample pictures can be a test picture sequence, and a preset threshold value is set through training and pre-analysis based on the calculated texture degrees.
In some embodiments, to reduce the computational complexity, the texture of the sample picture may also be downsampled, e.g., 1/2, 1/4 downsampled, before it is calculated, and the texture of the downsampled sample picture is calculated.
In step S520, the texture degree of the current picture is calculated, and the calculated texture degree is compared with a predetermined threshold value to determine the category of the current picture.
In some embodiments, the texture degree of the current picture may be calculated directly, or the texture degree of the downsampled current picture may be calculated.
By training and pre-analyzing the texture of the sample picture sequence, a predetermined threshold for determining the picture category can be set more accurately. In addition, the sample picture is downsampled before the texture degree is calculated, so that the calculation amount in the texture degree calculation can be saved.
Fig. 6A, 6B, and 6C are schematic diagrams illustrating the application of different deblocking filter filters according to embodiments of the present disclosure.
Fig. 6A to 6C show 3 boundary cases. The samples on both sides of the boundary of fig. 6A are flat and visually form a stronger blocking effect than in fig. 6B, and thus, the samples on both sides of the boundary of fig. 6A need to be strongly filtered to obtain a good visual effect. With respect to fig. 6C, since the sample distortion always falls within a certain range, when the difference between sample values at the boundary is very large, such a block boundary is caused by the picture sequence content itself, not a pseudo boundary. Therefore, only weak filtering needs to be applied to the block boundary in fig. 6C.
In some embodiments, in addition to the boundary threshold β, another boundary threshold t is set C To compare with the degree of variation and flatness between samples on both sides of the block boundary, respectively. The boundary threshold value beta and the boundary threshold value t are as follows C Respectively referred to as a first boundary threshold and a second boundary threshold.
The degree of variation and flatness between samples on both sides of a block boundary are calculated with reference to block boundary schematic between two adjacent blocks to which deblocking filtering is applied and equations (1) to (4) according to an embodiment of the present disclosure, and in the case where the following equations (9) to (14) are all satisfied (e.g., block boundary in fig. 6B), a strong filter is selected:
2(dp 0 +dq 0 )＜(β＞＞2) (9)
2(dp 3 +dq 3 )＜(β＞＞2) (10)
|p(3，0)-p(0，0)|+|q(0，0)-q(3，0)|＜(β＞＞3) (11)
|p(3，3)-p(0，3)|+|q(0，3)-q(3，3)|＜(β＞＞3) (12)
|p(0，0)-q(0，0)|＜(5t C +1)＞＞1 (13)
|p(0，3)-q(0，3)|＜(5t C +1)＞＞1 (14)
wherein, the operator "a > b" represents an arithmetic right shift, i.e., a right shift by b bits. Equations (9) and (10) represent the degree of change of two sample values of the block boundary. Equations (11) and (12) are used to determine whether samples of both block boundaries are flat. Equations (13) and (14) are used to determine whether the span of samples at the block boundary is controlled within a certain range.
Further, when at least one of equations (9) to (14) is not satisfied, such as the block boundary shown in fig. 6C, in which the difference between samples p (0, 0) and q (0, 0) on both sides of the boundary is large, equation (13) is not satisfied, a weak filter is selected.
In HEVC, a first boundary threshold β and a second boundary threshold t are derived with reference to the following table 1 based on quantization parameters QP of encoded blocks to which blocks on both sides of a block boundary belong, and a first offset value for a first boundary threshold and a second offset value for a second boundary threshold, respectively C . Wherein the first and second offset values are represented in the bitstream by syntax elements slice_beta_offset_div2 and slice_tc_offset_div2.
TABLE 1
| Q | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| β′ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 7 | 8 |
| t C ′ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| Q | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 |
| β′ | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 20 | 22 | 24 | 26 | 28 | 30 | 32 | 34 | 36 |
| t C ′ | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 3 | 4 | 4 | 4 |
| Q | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | |||
| β′ | 38 | 40 | 42 | 44 | 46 | 48 | 50 | 52 | 54 | 56 | 58 | 60 | 62 | 64 | - | - | |||
| t C ′ | 5 | 5 | 6 | 6 | 7 | 8 | 9 | 10 | 11 | 13 | 14 | 16 | 18 | 20 | 22 | 24 |
Specifically, let Qp P And Qp Q The quantization parameter QP of the encoded block to which the blocks P and Q belong, respectively, is obtained by the following equation (15) to obtain the variable qP L ：
qP L ＝(Qp P +Qp Q +1)＞＞1 (15)
To derive the first boundary threshold β, Q is calculated by the following equation (16):
Q＝Clip3(0，51，qP L +(slice_beta_offset_div2＜＜1) (16)
clip3 (x, y, z) is a clamp function, and z is limited to a range of x to y (inclusive). "a < b" means arithmetic shift left, i.e., shift left by b bits.
Beta' is derived with reference to table 1, and the first boundary threshold beta is derived based on the bit depth value of the luminance component by the following equation (17):
β＝β′*(1＜＜(BitDepth Y -8)) (17)
wherein, bitDepth Y The depth of the sample of the luminance array is specified. For the Main Profile (Main Profile) commonly used in HEVC, bitDepth Y =8, where β=β'.
Similarly, to derive the second boundary threshold t C Q is calculated by the following equation (18):
Q＝Clip3(0，53，qP L +2*(bS-1)+(slice_tc_offset_tc＜＜1)) (18)
deriving t 'with reference to Table 1' C And based on the bit depth value of the luminance component, deriving a second boundary threshold t by the following equation (19) C ：
t C ＝t′ C *(1＜＜(BitDepth Y -8)) (19)
In some embodiments, the encoder side adjusts the values of slice_beta_offset_div2 and slice_tc_offset_div2 and encodes slice_beta_offset_div2 and slice_tc_offset_div2 in the bitstream after determining the class of the current picture in the sequence based on a predetermined threshold.
Specifically, slice_beta_offset_div2 and slice_tc_offset_div2 are written into the slice segment header syntax:
slice_beta_offset_div2 and slice_tc_offset_div2 specify β and t for the current slice C The deblocking parameter offset (divided by 2). The values of slice_beta_offset_div2 and slice_tc_offset_div2 should be in the range of-6 to 6 (inclusive).
By predetermining the picture categories, setting different boundary threshold offset value combinations for different picture categories, the encoder can be prevented from traversing 13×13=169 possible boundary threshold offset value combinations for each picture to be deblock filtered.
In some embodiments, boundary threshold offset value combinations may be set, for example, as shown in table 2 below:
TABLE 2
| slice_beta_offset_div2 | slice_tc_offset_div2 | |
| High complexity | -2 | -2 |
| Moderate complexity | 0 | 0 |
| Low complexity | 2 | 2 |
Fig. 7 is a schematic diagram of applying deblocking filtering to a current picture according to an embodiment of the present disclosure.
An HEVC standard compliant encoder has an embedded HEVC decoder compliant with the HEVC standard to reconstruct pictures in a sequence of pictures and to store the reconstructed (and possibly also loop filtered, depending on whether loop filtering is enabled) pictures in a decoded picture buffer as reference pictures that may be used in inter-frame prediction. In fig. 7, a current picture 700 in an input picture sequence is predicted 710 resulting in a predicted picture 700' for the current picture 700. The prediction may be intra prediction or inter prediction. In inter prediction, as described above, the prediction unit is a prediction block, and for a current prediction block in a current picture, a reference picture is obtained from a decoded picture buffer according to a reference picture index, and a prediction block of the current prediction block is obtained based on a motion vector of the current prediction block.
Subsequently, the residual Δ700 between the current picture 700 and its predicted picture 700' is transformed/quantized 720 and inverse quantized/transformed 730 in sequence, resulting in a residual picture 700″ of the current picture 700.
The predicted picture 700 'and the residual picture 700 "are added by adder 740 to obtain the reconstructed picture 700'" of the current picture 700.
With deblocking filtering enabled, the reconstructed picture 700 '"is processed with the selected deblocking filter to obtain a filtered reconstructed picture 700'". The filtered reconstructed picture 700 "" may be further subjected to sample adaptive offset processing, depending on the value of the respective enable flag.
Fig. 8 is a schematic diagram of a deblocking filtering apparatus 800 for a sequence of pictures, according to embodiments of the present disclosure.
As shown in fig. 8, the deblocking filtering apparatus 800 includes a picture category determination module 810, an adjustment module 820, and a selection module 830.
The picture category determination module 810 determines a category of a current picture in the sequence based on a predetermined threshold. In some embodiments, the categories of pictures may include: a high complexity picture with e.g. a high speed moving object, a medium complexity picture with e.g. a low speed moving object, and a low complexity picture with a substantially constant background area.
The adjustment module 820 adjusts a boundary threshold for deblocking filtering a block boundary between two neighboring blocks within the current picture based on the determined category.
The selection module 830 selects a deblocking filter to be applied to the block boundary based on a boundary threshold.
In some embodiments, further, the degree of variation and the degree of flatness between samples located on both sides of the block boundary in two adjacent blocks are calculated, and a deblocking filter to be applied to the block boundary is selected based on the degree of variation and the degree of flatness and a boundary threshold. Depending on the degree of filtering, either a strong filter or a weak filter may be applied. The detailed process of deblocking filter selection will be described below.
The design of HEVC has followed a block-based hybrid video coding framework. First, each picture in an input picture sequence is divided into coding tree units. For a picture with three sample arrays, each coding tree unit consists of one luma sample coding tree block and two corresponding chroma sample coding tree blocks and syntax structures for coding the samples; for monochrome pictures, each coding tree unit consists of a block of sample coding trees and a syntax structure for coding the samples. Then, each coding tree block is subjected to recursive quadtree division to obtain a coding block which is a basic unit of intra/inter coding. Subsequently, the encoded blocks are used as tree roots of the prediction tree and the transform tree, one or more prediction blocks are divided via the indication of the division mode flag, and one or more transform blocks are obtained by the quadtree division. The prediction block is a unit on which the same prediction is performed, and the transform block is a unit on which the same transform is performed.
Deblocking filtering of HEVC deals with block boundaries in blocks of 8 x 8 size in all prediction blocks and transform blocks.
Deblocking filtering decisions in HEVC can be divided into 3 stages:
(1) Deriving a boundary filtering strength;
(2) A filtering switch decision;
(3) A deblocking filter is selected.
First, the boundary filter strength is derived. And preliminarily judging whether filtering and filtering parameters are needed according to the coding parameters of the boundary blocks. Discontinuities in sample values at block boundaries may result from neighboring blocks employing different coding parameters (e.g., different prediction modes, different reference pictures, different motion vectors, etc.).
Next, a filter switch decision is made. Discontinuous boundaries of flat areas of the picture are more easily observed due to the spatial masking effect of the human eye. When the sample values on both sides of the boundary are relatively smooth, but large differences occur at the boundary, the human visual system can clearly recognize such discontinuities at the boundary. Such discontinuities are not noticeable when the sample values on both sides of the boundary exhibit a highly variable trend. Therefore, it is necessary to adjust the boundary threshold to compare the degree of variation between samples on both sides of the block boundary with an appropriate boundary threshold to decide whether to perform deblocking filtering.
Specifically, taking a vertical block boundary as an example, a block boundary between two adjacent blocks to which deblocking filtering is applied according to an embodiment of the present disclosure is illustrated, and p (x, y), q (x, y) are sample values on both sides of the block boundary, respectively. Calculating the degree of change between samples on both sides of the block boundary by the following equations (1) to (4), wherein dp 0 Representing the degree of variation, dq, between samples of the first row in a P block 0 Representing the degree of variation, dp, between samples of the first row in a Q block 3 Representing the degree of variation between samples of the fourth row in the P block, and dq 3 Representing the degree of variation between samples of the fourth row in the Q block.
dp 0 ＝|p(2，0)-2p(1，0)+p(0，0)| (1)
dq 0 ＝|q(2，0)-2q(1，0)+q(0，0)| (2)
dp 3 ＝|p(2，3)-2p(1，3)+p(0，3)| (3)
dq 3 ＝|q(2，3)-2q(1，3)+q(0，3)| (4)
Further, the texture degree of the vertical block boundary is calculated by the following equation (5):
C B ＝dp 0 +dq 0 +dp 3 +dq 3 (5)
the larger the texture value of a block boundary region, the more uneven the region, and when the texture value is large to some extent, the deblocking filter switch may be turned off. Thus, a boundary threshold β is set in HEVC, which turns the filter switch of the block boundary on when the following equation (6) is satisfied, and off otherwise:
C B ＜β (6)
by predetermining the class of the picture before deblocking filtering the picture, thereby setting different boundary thresholds for different classes of pictures, the decision accuracy of whether and what deblocking filter is applied to the block boundary can be improved. In addition, different boundary thresholds are set for pictures of different categories based on predetermined picture categories, so that the calculation amount of traversing the combination of various boundary thresholds for each picture can be greatly reduced.
Further, the deblocking filter apparatus 800 may further include a first calculation module, a setting module, a second calculation module, and a comparison module.
The first calculation module calculates the texture degrees of the plurality of sample pictures, and the setting module sets a predetermined threshold value based on the calculated texture degrees.
In some embodiments, the texture degree μ of each sample picture may be calculated by the variance of the gray level histogram of the picture 2 (z)：
Where z is the gray scale of the picture, p (z i ) Is the corresponding histogram, L is the number of different gray levels, and m is the mean of z:
the texture degree calculation is performed on a plurality of sample pictures, wherein the sample pictures can be a test picture sequence, and a preset threshold value is set through training and pre-analysis based on the calculated texture degrees.
In some embodiments, to reduce the computational complexity, the texture of the sample picture may also be downsampled, e.g., 1/2, 1/4 downsampled, before it is calculated, and the texture of the downsampled sample picture is calculated.
The second calculation module calculates the texture degree of the current picture and the comparison module compares the calculated texture degree with a predetermined threshold to determine the class of the current picture by the picture class determination module 810.
In some embodiments, the texture degree of the current picture may be calculated directly, or the texture degree of the downsampled current picture may be calculated.
By training and pre-analyzing the texture of the sample picture sequence, a predetermined threshold for determining the picture category can be set more accurately. In addition, the sample picture is downsampled before the texture degree is calculated, so that the calculation amount in the texture degree calculation can be saved.
According to the embodiment of the disclosure, for the case that the sample values at two sides of the block boundary are flat, a stronger blocking effect is formed visually, so that the samples at two sides of the block boundary need to be strongly filtered to obtain a good visual effect. In the case where the difference between the sample values at the block boundaries is very large, such block boundaries are caused by the picture sequence content itself, not the pseudo-boundaries, since the sample distortion will always be within a certain range. Therefore, only weak filtering needs to be applied to the block boundary.
In some embodiments, in addition to the boundary threshold β, another boundary threshold t is set C To compare with the degree of variation and flatness between samples on both sides of the block boundary, respectively. The boundary threshold value beta and the boundary threshold value t are as follows C Respectively referred to as a first boundary threshold and a second boundary threshold.
The degree of variation and flatness between samples on both sides of a block boundary are calculated with reference to block boundary illustration between two adjacent blocks to which deblocking filtering is applied and equations (1) to (4) according to an embodiment of the present disclosure, and in the case where the following equations (9) to (14) are all satisfied (for example, when the sample values on both sides of the block boundary are flat), a strong filter is selected:
2(dp 0 +dq 0 )＜(β＞＞2) (9)
2(dp 3 +dq 3 )＜(β＞＞2) (10)
|p(3，0)-p(0，0)|+|q(0，0)-q(3，0)|＜(β＞＞3) (11)
|p(3，3)-p(0，3)|+|q(0，3)-q(3，3)|＜(β＞＞3) (12)
|p(0，0)-q(0，0)|＜(5t C +1)＞＞1 (13)
|p(0，3)-q(0，3)|＜(5t C +1)＞＞1 (14)
wherein, the operator "a > b" represents an arithmetic right shift, i.e., a right shift by b bits. Equations (9) and (10) represent the degree of change of two sample values of the block boundary. Equations (11) and (12) are used to determine whether samples of both block boundaries are flat. Equations (13) and (14) are used to determine whether the span of samples at the block boundary is controlled within a certain range.
Further, when at least one of equations (9) to (14) is not satisfied, for example, when the difference between samples p (0, 0) and q (0, 0) on both sides of the block boundary is large, equation (13) is not satisfied, a weak filter is selected.
In HEVC, a first boundary threshold β and a second boundary threshold t are derived with reference to the following table 1 based on quantization parameters QP of encoded blocks to which blocks on both sides of a block boundary belong, and a first offset value for a first boundary threshold and a second offset value for a second boundary threshold, respectively C . Wherein the first and second offset values are represented in the bitstream by syntax elements slice_beta_offset_div2 and slice_tc_offset_div2.
TABLE 1
| Q | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| β′ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 7 | 8 |
| t C ′ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| Q | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 |
| β′ | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 20 | 22 | 24 | 26 | 28 | 30 | 32 | 34 | 36 |
| t C ′ | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 3 | 4 | 4 | 4 |
| Q | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | |||
| β′ | 38 | 40 | 42 | 44 | 46 | 48 | 50 | 52 | 54 | 56 | 58 | 60 | 62 | 64 | - | - | |||
| t C ′ | 5 | 5 | 6 | 6 | 7 | 8 | 9 | 10 | 11 | 13 | 14 | 16 | 18 | 20 | 22 | 24 |
Specifically, let Qp P And Qp Q The quantization parameter QP of the encoded block to which the blocks P and Q belong, respectively, is obtained by the following equation (15) to obtain the variable qP L ：
qP L ＝(Qp P +Qp Q +1)＞＞1 (15)
To derive the first boundary threshold β, Q is calculated by the following equation (16):
Q＝Clip3(0，51，qP L +(slice_beta_offset_div2＜＜1) (16)
clip3 (x, y, z) is a clamp function, and z is limited to a range of x to y (inclusive). "a < b" means arithmetic shift left, i.e., shift left by b bits.
Beta' is derived with reference to table 1, and the first boundary threshold beta is derived based on the bit depth value of the luminance component by the following equation (17):
β＝β′*(1＜＜(BitDepth Y -8)) (17)
wherein, bitDepth Y The depth of the sample of the luminance array is specified. For the Main Profile (Main Profile) commonly used in HEVC, bitDepth Y =8, where β=β'.
Similarly, to derive the second boundary threshold t C Q is calculated by the following equation (18):
Q＝Clip3(0，53，qP L +2*(bS-1)+(slice_tc_offset_tc＜＜1)) (18)
deriving t 'with reference to Table 1' C And based on the bit depth value of the luminance component, deriving a second boundary threshold t by the following equation (19) C ：
t C ＝t′ C *(1＜＜(BitDepth Y -8)) (19)
In some embodiments, the encoder side adjusts the values of slice_beta_offset_div2 and slice_tc_offset_div2 and encodes slice_beta_offset_div2 and slice_tc_offset_div2 in the bitstream after determining the class of the current picture in the sequence based on a predetermined threshold.
Specifically, slice_beta_offset_div2 and slice_tc_offset_div2 are written into the slice segment header syntax:
slice_beta_offset_div2 and slice_tc_offset_div2 specify β and t for the current slice C The deblocking parameter offset (divided by 2). The values of slice_beta_offset_div2 and slice_tc_offset_div2 should be in the range of-6 to 6 (inclusive).
By predetermining the picture categories, setting different boundary threshold offset value combinations for different picture categories, the encoder can be prevented from traversing 13×13=169 possible boundary threshold offset value combinations for each picture to be deblock filtered.
In some embodiments, boundary threshold offset value combinations may be set, for example, as shown in table 2 below:
TABLE 2
| slice_beta_offset_div2 | slice_tc_offset_div2 | |
| High complexity | -2 | -2 |
| Moderate complexity | 0 | 0 |
| Low complexity | 2 | 2 |
Fig. 9 shows a schematic block diagram of an example electronic device 900 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 9, the apparatus 900 includes a computing unit 901 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 902 or a computer program loaded from a storage unit 908 into a Random Access Memory (RAM) 903. In the RAM903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM903 are connected to each other by a bus 904. An input/output (I/O) interface 905 is also connected to the bus 904.
Various components in device 900 are connected to I/O interface 905, including: an input unit 906 such as a keyboard, a mouse, or the like; an output unit 907 such as various types of displays, speakers, and the like; a storage unit 908 such as a magnetic disk, an optical disk, or the like; and a communication unit 909 such as a network card, modem, wireless communication transceiver, or the like. The communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunications networks.
The computing unit 901 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 901 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 performs the various methods and processes described above, such as method 100 or 500. For example, in some embodiments, the methods described above may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 900 via the ROM 902 and/or the communication unit 909. When the computer program is loaded into RAM903 and executed by the computing unit 901, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service ("Virtual Private Server" or simply "VPS") are overcome. The server may also be a server of a distributed system or a server that incorporates a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (11)
1. A deblocking filtering method for a sequence of pictures, comprising:
determining a category of a current picture in the sequence based on a predetermined threshold, wherein the category is one of a high complexity picture, a medium complexity picture, and a low complexity picture;
setting corresponding boundary threshold offset value combinations for the determined picture types to adjust boundary thresholds for deblocking filtering of block boundaries between two adjacent blocks in the current picture; and
a deblocking filter to be applied to the block boundary is selected based on the boundary threshold.
2. The method of claim 1, wherein the boundary threshold offset value combination is for a slice in the current picture.
3. The method of claim 2, wherein the boundary threshold comprises a first boundary threshold and a second boundary threshold, and the boundary threshold offset value combination comprises a first boundary threshold offset value for the first boundary threshold and a second boundary threshold offset value for the second boundary threshold, wherein the first boundary threshold offset value and the second boundary threshold offset value are represented in a bitstream by syntax elements slice_beta_offset_div2 and slice_tc_offset_div2.
4. A method according to claim 3, further comprising:
calculating the degree of change and flatness between samples located on two sides of the block boundary in the two adjacent blocks; and
a deblocking filter to be applied to the block boundary is selected based on the degree of variation and the degree of flatness, and the first boundary threshold and the second boundary threshold.
5. The method of claim 1, further comprising:
predicting the current picture to obtain a predicted picture aiming at the current picture;
sequentially carrying out transformation/quantization and inverse quantization/inverse transformation on the residual error between the current picture and the predicted picture to obtain a residual error picture of the current picture;
obtaining a reconstructed picture of the current picture based on the predicted picture and the residual picture; and
the reconstructed slice is processed with the deblocking filter to obtain a filtered reconstructed picture.
6. A deblocking filtering apparatus for a sequence of pictures, comprising:
the picture category determining module is used for determining the category of the current picture in the sequence based on a preset threshold value, wherein the category is one of a high-complexity picture, a medium-complexity picture and a low-complexity picture;
the adjusting module is used for setting corresponding boundary threshold offset value combinations aiming at the determined picture types so as to adjust boundary thresholds for deblocking filtering on block boundaries between two adjacent blocks in the current picture; and
a selection module selects a deblocking filter to be applied to the block boundary based on the boundary threshold.
7. The apparatus of claim 6, wherein the boundary threshold offset value combination is for a slice in the current picture.
8. The apparatus of claim 7, wherein the boundary threshold comprises a first boundary threshold and a second boundary threshold, and the boundary threshold offset value combination comprises a first boundary threshold offset value for the first boundary threshold and a second boundary threshold offset value for the second boundary threshold, wherein the first boundary threshold offset value and the second boundary threshold offset value are represented in a bitstream by syntax elements slice_beta_offset_div2 and slice_tc_offset_div2.
9. The apparatus of claim 8, further comprising:
a third calculation module for calculating the degree of variation and flatness between samples located at both sides of the block boundary in the two adjacent blocks; and
the selection module selects a deblocking filter to be applied to the block boundary based on the degree of variation and the degree of flatness, and the first boundary threshold and the second boundary threshold.
10. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
11. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-5.
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