CN114786010A - Rate distortion optimization quantization method and device, storage medium and electronic equipment - Google Patents
Rate distortion optimization quantization method and device, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN114786010A CN114786010A CN202210225735.9A CN202210225735A CN114786010A CN 114786010 A CN114786010 A CN 114786010A CN 202210225735 A CN202210225735 A CN 202210225735A CN 114786010 A CN114786010 A CN 114786010A
- Authority
- CN
- China
- Prior art keywords
- subunit
- minimum
- transform
- unit
- transformation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000013139 quantization Methods 0.000 title claims abstract description 113
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000005457 optimization Methods 0.000 title abstract description 22
- 230000009466 transformation Effects 0.000 claims abstract description 87
- 230000015654 memory Effects 0.000 claims description 21
- 238000004590 computer program Methods 0.000 claims description 13
- 238000006243 chemical reaction Methods 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000007781 pre-processing Methods 0.000 claims description 5
- 108010001267 Protein Subunits Proteins 0.000 claims description 4
- 230000006870 function Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 abstract description 5
- 238000011002 quantification Methods 0.000 abstract description 3
- 230000008569 process Effects 0.000 description 14
- 238000010586 diagram Methods 0.000 description 9
- 238000004422 calculation algorithm Methods 0.000 description 8
- 238000004891 communication Methods 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
Images
Classifications
-
- 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
- H04N19/102—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
- H04N19/129—Scanning of coding units, e.g. zig-zag scan of transform coefficients or flexible macroblock ordering [FMO]
-
- 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
- H04N19/146—Data rate or code amount at the encoder output
- H04N19/147—Data rate or code amount at the encoder output according to rate distortion criteria
-
- 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
- H04N19/18—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 a set of transform coefficients
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
Abstract
The invention discloses a rate distortion optimization quantification method, a rate distortion optimization quantification device, a storage medium and electronic equipment. Wherein, the method comprises the following steps: dividing all minimum subunits of a transformation unit in a video frame to obtain a transformation subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; determining a representative value of the quantized coefficients of each of the transform subunits; based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning; taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set; and outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set. The invention solves the technical problems that the RDOQ module in the related technology needs to consume a large amount of coding time and the video coding efficiency is low.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a rate distortion optimization quantization method, a rate distortion optimization quantization device, a storage medium and electronic equipment.
Background
Rate Distortion Optimized Quantization (RDOQ) is a very important technology in the AVS3 video coding standard, and can effectively improve the performance of an encoder, but the conventional RDOQ module needs to calculate the Rate-Distortion Cost (RD-Cost) of all coefficients in a transform unit, and this process has high computational complexity, so that the RDOQ module needs to consume a large amount of coding time, and the video coding efficiency is low.
Disclosure of Invention
The embodiment of the invention provides a rate-distortion optimization quantization method, a rate-distortion optimization quantization device, a storage medium and electronic equipment, and aims to at least solve the technical problems that an RDOQ module in the related art needs to consume a large amount of coding time and the video coding efficiency is low.
According to an aspect of the embodiments of the present invention, there is provided a quantization method for rate distortion optimization, including: dividing all minimum subunits of a transformation unit in a video frame to obtain a transformation subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; determining a representative value of the quantization coefficients of each of the transform sub-units; based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning; taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set; and outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
According to another aspect of the embodiments of the present invention, there is also provided a rate-distortion optimization quantization apparatus, including: the dividing unit is used for dividing all the minimum subunits of the conversion unit in the video frame to obtain a conversion subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; a first determining unit configured to determine a representative value of the quantized coefficient of each of the transform sub-units; a calculating unit, configured to sequentially calculate, based on the representative value, a first code rate distortion cost corresponding to each transform subunit when each transform subunit is used as a last non-zero coefficient unit for zigzag scanning; the second determining unit is used for taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set; and the first output unit is used for outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
According to still another aspect of the embodiments of the present invention, there is also provided an electronic device, including a memory and a processor, where the memory stores a computer program, and the processor is configured to execute the above rate-distortion optimization quantization method through the computer program.
According to a further aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above rate-distortion optimized quantization method when running.
In the embodiment of the invention, all the minimum subunits of the conversion units in the video frame are divided to obtain a conversion subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; determining a representative value of the quantized coefficients of each of the transform subunits; based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning; taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set; in the method, because the representative value of the quantization coefficient of each transformation subunit is adopted, and final non-zero coefficient position decision is not required to be carried out on all the quantization coefficients in the transformation unit, the calculation complexity of the RDOQ process in the AVS3 is reduced, the coding efficiency of the RDOQ algorithm is improved, and the technical problems that in the related technology, a large amount of coding time needs to be consumed by an RDOQ module, and the video coding efficiency is low are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic diagram of an application environment of an alternative rate-distortion optimized quantization method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an application environment of an alternative rate-distortion optimized quantization method according to an embodiment of the present invention;
FIG. 3 is a flow chart diagram of an alternative rate-distortion optimized quantization method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating the operation of an alternative rate-distortion optimized quantization method according to an embodiment of the present invention;
fig. 5 is an operational schematic diagram of an alternative rate-distortion optimized quantization method according to an embodiment of the present invention;
fig. 6 is a flow chart diagram of an alternative rate-distortion optimized quantization method according to an embodiment of the present invention;
fig. 7 is a schematic diagram of an alternative rate-distortion optimized quantization apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an alternative electronic device according to an embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in other sequences than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an aspect of the embodiments of the present invention, there is provided a rate-distortion optimization quantization method, which may be applied, but not limited, to the application environment shown in fig. 1 as an optional implementation manner. The application environment comprises: the terminal equipment 102, the network 104 and the server 106 are in man-machine interaction with a user. The user 108 and the terminal device 102 can perform human-computer interaction, and a rate-distortion optimization quantification application program runs in the terminal device 102. The terminal 102 includes a human interaction screen 1022, a processor 1024, and a memory 1026. The human-computer interaction screen 1022 is used to present transform units in video frames; processor 1024 is configured to obtain transform units in video frames. The memory 1026 is configured to store the set of transform subunits, the set of target transform subunits, and the target quantization coefficients corresponding to each minimum subunit.
In addition, the server 106 includes a database 1062 and a processing engine 1064, where the database 1062 is used to store the above-mentioned transformation subunit set, the target transformation subunit set, and the target quantization coefficient corresponding to each minimum subunit. Processing engine 1064 is configured to divide all minimum subunits of a transform unit in a video frame to obtain a transform subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; determining a representative value of the quantization coefficients of each of the transform sub-units; based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning; taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set; outputting a target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set; and sending the target quantization factor to the client of the terminal device 102.
In one or more embodiments, the rate-distortion optimized quantization method described above in this application may be applied in the application environment shown in fig. 2. As shown in fig. 2, a user 202 may interact with a user device 204. The user device 204 includes a memory 206 and a processor 208. The user device 204 in this embodiment may refer to, but is not limited to, the operation performed by the terminal device 102 to output the target quantization coefficient corresponding to each minimum subunit in the target transform subunit set.
Optionally, the terminal device 102 and the user device 204 include, but are not limited to, at least one of the following: mobile phones (such as Android Mobile phones, iOS Mobile phones, etc.), notebook computers, tablet computers, palm computers, MID (Mobile Internet Devices), PAD, desktop computers, smart televisions, etc. The target client may be a video client, an instant messaging client, a browser client, an educational client, etc. The network 104 may include, but is not limited to: a wired network, a wireless network, wherein the wired network comprises: a local area network, a metropolitan area network, and a wide area network, the wireless network comprising: bluetooth, WIFI, and other networks that enable wireless communication. The server 106 may be a single server, a server cluster composed of a plurality of servers, or a cloud server. The above is merely an example, and this is not limited in this embodiment.
As an alternative implementation manner, as shown in fig. 3, an embodiment of the present invention provides a rate-distortion optimization quantization method, including the following steps:
s302, dividing all minimum subunits of a conversion unit in a video frame to obtain a conversion subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits.
In the related art, as shown in fig. 4 (b), for a Transform Unit (TU) containing n quantized coefficients, determining a final non-zero coefficient position by zigzag scanning requires traversing each minimum sub-Unit. The basic processing unit of the RDOQ algorithm in the AVS3 coding standard contains TUs with all quantized coefficients, as shown in fig. 4, the TU in fig. 4 (a) includes 4 × 4 minimum sub-units, each minimum sub-unit including one quantized coefficient.
In the embodiment of the present invention, all minimum sub-units of a transform unit in a video frame are divided to obtain a transform sub-unit set, as shown in fig. 5, a TU in (a) in fig. 4 includes 4 × 4 minimum sub-units, which are divided equally to obtain a transform sub-unit set including 2 × 2 transform sub-units, where each transform sub-unit includes 4 minimum sub-units.
S304, a representative value of the quantized coefficients of each of the transform subunits is determined.
In the embodiment of the present invention, since each transform subunit includes a plurality of minimum subunits, the representative value of the quantized coefficients of each transform subunit may be represented by an average value of the quantized coefficients of the plurality of minimum subunits included in the transform subunit, or a transformed value of the average value.
And S306, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of the zigzag scanning based on the representative values.
Specifically, as shown in fig. 5, for example, the transform subunit 502 is used as the last non-zero coefficient unit of the zigzag scan, that is, the remaining 3 transform subunits are discarded, and the first rate distortion cost corresponding to the transform unit is calculated, where the first rate distortion cost corresponding to the transform unit is the rate distortion cost corresponding to the transform subunit 502.
And S308, taking the transformation subunit set corresponding to the zigzag scanning with the minimum first code rate distortion cost as a target transformation subunit set.
In the embodiment of the present invention, as shown in fig. 5, for example, the set of transform subunits corresponding to the zigzag scan with the smallest distortion cost of the first code rate includes the transform subunit 502 and the transform subunit on the right side of the transform subunit 502.
And S310, outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
Specifically, as shown in fig. 5, for example, the zigzag scan corresponding to the smallest first rate distortion cost includes the transformation sub-unit 502 and the transformation sub-unit on the right side of the transformation sub-unit 502, and then the target quantization coefficients corresponding to the smallest sub-unit included in the transformation sub-unit 502 and the transformation sub-unit on the right side of the transformation sub-unit 502 are output.
In the related art, as shown in fig. 4 (b), all coefficients in a CU with a size of 4 × 4 are subjected to the final non-zero coefficient position decision, and 16 zigzag code scanning passes are required, as shown in fig. 5, from the transform subunit 502 to the last transform subunit, whereas the embodiment of the present invention only needs 4 zigzag scanning.
In the embodiment of the invention, all the minimum subunits of the transform units in the video frame are divided to obtain a transform subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; determining a representative value of the quantization coefficients of each of the transform sub-units; based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning; taking a transformation subunit set corresponding to the zigzag scanning with the minimum first code rate distortion cost as a target transformation subunit set; in the method, because the representative value of the quantization coefficient of each transformation subunit is adopted, and the final non-zero coefficient position decision is not needed to be carried out on all the quantization coefficients in the transformation unit, the calculation complexity of the RDOQ process in the AVS3 is reduced, the coding efficiency of the RDOQ algorithm is improved, and the technical problems that the RDOQ module in the related technology needs to consume a large amount of coding time and the video coding efficiency is low are solved.
In one or more embodiments, the determining the representative value of the quantized coefficient of each transform subunit includes:
and taking the average value of the quantized coefficients of all the minimum sub-units in each transform sub-unit as the representative value.
In the embodiment of the present invention, the average value of the quantized coefficients of all the smallest sub-units in each transform sub-unit is used as the representative value, so that the video encoding speed can be increased.
In one or more embodiments, the first code rate distortion cost corresponding to each transform subunit when each transform subunit is used as the last non-zero coefficient unit of the zigzag scanning is sequentially calculated and obtained through formulas (1), (2), (3):
Jj,coded＝Dcoded,j+λ·Rcoded,j； (2)
Jj,uncoded＝Duncoded,j+λ·Runcoded,j； (3)
wherein, Ji,islastRepresenting the first rate distortion cost, J, of the current transform subunit as the last non-zero coefficient unitj,codedRepresenting the rate-distortion cost, J, required to encode the quantized coefficients of the current transform subunitj,uncodedRepresenting the rate-distortion cost, D, required to truncate the quantized coefficientscoded,j，Duncoded,jRespectively correspondingly encoding the current quantized coefficients and truncating the currentQuantizing distortion parameters of the coefficients; rcoded,j，Runcoded,jAnd lambda is Lagrange coefficient, corresponding to the code rate of coding the current quantization coefficient and truncating the current quantization coefficient respectively.
In one or more embodiments, before dividing all minimum sub-units of a transform unit in a video frame to obtain a transform sub-unit set, the method includes:
acquiring an initial quantization coefficient corresponding to each minimum subunit of a transformation unit;
processing the initial quantization coefficients by formula (4) to obtain preprocessed quantization coefficients corresponding to each of the initial quantization coefficients:
the method comprises the following steps of obtaining a PQCoeff, a TranCoeff and a Qstep, wherein the PQCoeff is a preprocessing quantization coefficient, the TranCoeff is an initial quantization coefficient, Round is a rounding operation function, and the Qstep is a quantization step;
and obtaining the quantization coefficient of each minimum subunit based on the preprocessed quantization coefficients.
In one or more embodiments, the obtaining the quantized coefficient of each minimum sub-unit based on the preprocessed quantized coefficients includes:
respectively calculating a second code rate distortion cost required by the preprocessing quantization coefficient, the first reference quantization coefficient and the second reference quantization coefficient corresponding to each minimum subunit; and taking the value with the minimum second code rate distortion cost as the quantization coefficient of the current minimum subunit.
In the embodiment of the present invention, the preprocessed quantized coefficient corresponding to the smallest sub-unit is qiFor example, the first reference quantization coefficient may be qi-1 and the second reference quantized coefficient is 0. Respectively calculating the preprocessed quantized coefficients q corresponding to each minimum subunitiFirst reference quantized coefficient qi-1, the rate distortion cost required for the second reference quantization coefficient to be 0; taking the value with the minimum code rate distortion cost asThe above quantized coefficients of the previous minimum sub-unit.
By comparing the code rate distortion cost of the preprocessed quantized coefficient corresponding to the minimum subunit with that of different reference quantized coefficients, the distortion rate of image coding can be reduced, and the accuracy of image coding is improved.
In one or more embodiments, the rate-distortion optimized quantization method further includes: and outputting the scanning position information corresponding to each minimum subunit in the target transformation subunit set.
In the embodiment of the present invention, as shown in fig. 5, for example, the transformation subunit set corresponding to the zigzag scanning with the minimum first rate distortion cost includes the transformation subunit 502, at this time, the transformation subunit 502 is output, and scanning position information corresponding to the minimum subunit included in the transformation subunit 502, for example, position information (0, 1, 2, 4) of the minimum subunit is output.
Based on the foregoing embodiments, as shown in fig. 6, in an application embodiment, the rate-distortion optimization quantization method further includes the following steps:
s602, for all coefficient sets TransCoeff in a transform block after video frame transformation, firstly, pre-quantizing the coefficient sets TransCoeff according to the following formula to obtain a pre-quantized coefficient set PQCoeff:
S604, for each coefficient q in PQCoeffiIt is changed to q by calculating it respectively as followsi， q i1, and 0, the rate-distortion Cost required for the three values (RD-Cost):
RD-Cost(qi)＝D(qi)+λ·R(qi)
and taking the minimum value of RD-Cost as the optimal coefficient of the current position i of the minimum subunit in the transformation block, and obtaining an optimal quantization coefficient set OptimalCoeff after all quantization coefficients in PQCoeff are determined.
S606, for posts in OptimalCoeffWith non-zero quantised coefficients liCalculating liRD-Cost as the last non-zero quantized coefficient, where RD-Cost is the smallest liThe corresponding zigzag scanning coordinate i is the final nonzero coefficient coordinate and is marked as LastNzPos.
And S608, finally, directly setting the quantization coefficients corresponding to the minimum subunit of which all Z-shaped scanning coordinates are larger than LastNzPos to zero, and outputting a final quantization result QuantCoeff.
In the above flow, all the processes of the quantized coefficients are performed in the order shown in fig. 2, as shown in (a) of fig. 2, the size of the parameter i represents the processing order of the corresponding position coefficient in the TU, and (b) of fig. 2 shows the data processing flow in the whole TU. In the RDOQ process, the final non-zero coefficient position process needs to calculate the code rate distortion cost J of all quantization coefficients in the whole TU as the final non-zero coefficient one by onei,islastThe calculation formula is as follows:
Jj,coded＝Dcoded,j+λ·Rcoded,j； (2)
Jj,uncoded＝Duncoded,j+λ·Runcoded,j； (3)
wherein, Ji,islastRepresenting the first rate distortion cost, J, of the current transform subunit as the last non-zero coefficient unitj,codedRepresenting the rate-distortion cost, J, required to encode the quantized coefficients of the current transform subunitj,uncodedRepresenting the rate-distortion cost, D, required to truncate the quantized coefficientcoded,j，Duncoded,jRespectively correspondingly encoding the current quantization coefficient and eliminating the distortion parameter of the current quantization coefficient; rcoded,j，Runcoded,jAnd lambda is Lagrange coefficient, corresponding to the code rate of coding the current quantization coefficient and truncating the current quantization coefficient respectively.
And (3) calculating to obtain all quantization coefficients in the whole TU as the code rate distortion cost of the final non-zero coefficient according to the formulas (1), (2) and (3).
Determining the last non-zero coefficient is a high computational complexity process, a maximum of 64x64 TUs is supported in the AVS3 video coding standard, the last non-zero coefficient process needs to be decided for all 4096 coefficients in the original algorithm, and a large amount of coding time is consumed.
In order to reduce the amount of calculation in the process of deciding the last non-zero Coefficient, in the rate distortion optimization quantization algorithm based on the Coefficient Group (CG), as shown in fig. 5, each TU is divided into CGs (minimum sub-units 502) including four coefficients, the four coefficients in each CG are averaged to obtain a CG representative value, and the CG representative value is substituted into the above formulas (1), (2) and (3) for calculation. And calculating to obtain the CG with the lowest cost, and then processing the CG by coefficients one by one.
The embodiment of the invention also has the following beneficial effects:
compared with the prior art, the method can obtain better coding quality and can obtain similar coding speed improvement. In the conventional RDOQ process, as shown in fig. 2 (b), for a TU with n coefficients, if the time required to determine a last non-zero coefficient position is t, the time required for the conventional RDOQ to determine all coefficients is n × t. In the invention, a fast algorithm based on CG is adopted, the final non-zero coefficient position determination is not required to be carried out on all coefficients in TU, the first pass of coarse screening aiming at CG only needs to use time n t/4, the total determination time is 4t + n t/4, the total saving time is (3n-16) t/4, the minimum value of n in AVS3 is 16, and the maximum value is 4096, the invention embodiment can greatly save the encoding time of the algorithm, under the configuration of AVS3 reference software HPM4.0.1 platform, 100 frames of Low Delay P (LDP) and Random Access (RA), 15 groups of sequences recommended to AVS3 standard group are tested, the Quantization parameters (Quantization Parameter, QP 38 and 45) are 27, 32, QP 38 and 45, the BD-rate performance losses are respectively 0.1% and 0%, when BD-e is negative, the BD-rate represents the same condition of Signal Noise R, the code rate is reduced, and the performance is improved; positive values are code rate increases and performance decreases. The larger the PSNR between two images, the more similar.
It should be noted that for simplicity of description, the above-mentioned method embodiments are shown as a series of combinations of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art will appreciate that the embodiments described in this specification are presently preferred and that no acts or modules are required by the invention.
According to another aspect of the embodiments of the present invention, there is also provided a rate-distortion optimized quantization apparatus for implementing the above rate-distortion optimized quantization method. As shown in fig. 7, the apparatus includes:
a dividing unit 702, configured to divide all minimum sub-units of a transform unit in a video frame to obtain a transform sub-unit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits;
a first determining unit 704 for determining a representative value of the quantized coefficients of each of the above transform subunits;
a calculating unit 706, configured to sequentially calculate, based on the representative value, a first code rate distortion cost corresponding to each transform subunit when each transform subunit is used as a last non-zero coefficient unit of the zigzag scan;
a second determining unit 708, configured to use a transformation subunit set corresponding to the zigzag scanning with the minimum first code rate distortion cost as a target transformation subunit set;
a first output unit 710, configured to output a target quantization coefficient corresponding to each minimum subunit in the target transform subunit set.
In the embodiment of the invention, all the minimum subunits of the transform units in the video frame are divided to obtain a transform subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits; determining a representative value of the quantized coefficients of each of the transform subunits; based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning; taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set; in the method, because the representative value of the quantization coefficient of each transformation subunit is adopted, and the final non-zero coefficient position decision is not needed to be carried out on all the quantization coefficients in the transformation unit, the calculation complexity of the RDOQ process in the AVS3 is reduced, the coding efficiency of the RDOQ algorithm is improved, and the technical problems that the RDOQ module in the related technology needs to consume a large amount of coding time and the video coding efficiency is low are solved.
In one or more embodiments, the first determining unit 704 specifically includes:
and a first determining module, configured to use an average value of the quantized coefficients of all the smallest sub-units in each of the transform sub-units as the representative value.
In one or more embodiments, the calculating unit 706 includes: a calculating module, configured to obtain a first rate distortion cost corresponding to the transforming unit according to the following formula:
Jj,coded＝Dcoded,j+λ·Rcoded,j； (2)
Jj,uncoded＝Duncoded,j+λ·Runcoded,j； (3)
wherein, Ji,islastRepresenting the first rate distortion cost, J, of the current transform subunit as the last non-zero coefficient unitj,codedRepresenting the rate-distortion cost, J, required to encode the quantized coefficients of the current transform subunitj,uncodedRepresenting the rate-distortion cost, D, required to truncate the quantized coefficientcoded,j，Duncoded,jRespectively correspondingly encoding the current quantization coefficient and eliminating the distortion parameter of the current quantization coefficient; rcoded,j，Runcoded,jAnd respectively correspondingly coding the current quantization coefficient and truncating the code rate of the current quantization coefficient, wherein lambda is a Lagrange coefficient.
In one or more embodiments, the rate-distortion optimized quantization apparatus further includes:
a first obtaining unit, configured to obtain an initial quantization coefficient corresponding to each minimum subunit of the transform unit;
a preprocessing unit, configured to process the initial quantized coefficients according to formula (4) to obtain preprocessed quantized coefficients corresponding to each of the initial quantized coefficients:
the method comprises the following steps of obtaining a PQCoeff, a TranCoeff and a Qstep, wherein the PQCoeff is a preprocessing quantization coefficient, the TranCoeff is an initial quantization coefficient, Round is a rounding operation function, and the Qstep is a quantization step;
a second obtaining unit, configured to obtain the quantized coefficient of each minimum sub-unit based on the preprocessed quantized coefficients.
In one or more embodiments, the second obtaining unit includes:
the first calculation module is used for calculating a second code rate distortion cost required by the preprocessed quantized coefficient, the first reference quantized coefficient and the second reference quantized coefficient corresponding to each minimum subunit;
and a second determining module, configured to use the value with the minimum second rate-distortion cost as the quantization coefficient of the current minimum subunit.
In one or more embodiments, the rate-distortion optimization quantization apparatus further includes:
and the second output unit is used for outputting the scanning position information corresponding to each minimum subunit in the target transformation subunit set.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device for implementing the above rate-distortion optimization quantization method, where the electronic device may be a terminal device or a server shown in fig. 8. The present embodiment takes the electronic device as an example for explanation. As shown in fig. 8, the electronic device comprises a memory 802 and a processor 804, the memory 802 having a computer program stored therein, the processor 804 being arranged to perform the steps of any of the above-described method embodiments by means of the computer program.
Optionally, in this embodiment, the electronic device may be located in at least one network device of a plurality of network devices of a computer network.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, dividing all minimum subunits of the conversion units in the video frame to obtain a conversion subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits;
s2, determining a representative value of the quantized coefficients of each of the transform sub-units;
s3, sequentially calculating a first code rate distortion cost corresponding to each transform subunit when each transform subunit is used as a last non-zero coefficient unit of zigzag scanning based on the representative values;
s4, taking the transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set;
and S5, outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
Alternatively, it can be understood by those skilled in the art that the structure shown in fig. 8 is only an illustration, and the electronic device may also be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, a Mobile Internet Device (MID), a PAD, and the like. Fig. 8 is a diagram illustrating a structure of the electronic apparatus. For example, the electronics may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 8, or have a different configuration than shown in FIG. 8.
The memory 802 may be used to store software programs and modules, such as program instructions/modules corresponding to the rate distortion optimization quantization method and apparatus in the embodiments of the present invention, and the processor 804 executes various functional applications and data processing by running the software programs and modules stored in the memory 802, so as to implement the above rate distortion optimization quantization method. The memory 802 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 802 can further include memory located remotely from the processor 804, which can be connected to the terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 802 may be, but not limited to, specifically configured to store information such as a target quantization coefficient. As an example, as shown in fig. 8, the memory 802 may include, but is not limited to, a dividing unit 702, a first determining unit 704, a calculating unit 706, a second determining unit 708, and a first output unit 710 in the rate-distortion optimization quantizing apparatus. In addition, other module units in the above-mentioned rate-distortion optimization quantization apparatus may also be included, but are not limited to them, and are not described in detail in this example.
Optionally, the transmitting device 806 is configured to receive or transmit data via a network. Examples of the network may include a wired network and a wireless network. In one example, the transmission device 806 includes a Network adapter (NIC) that can be connected to a router via a Network cable and other Network devices to communicate with the internet or a local area Network. In one example, the transmission device 806 is a Radio Frequency (RF) module, which is used to communicate with the internet via wireless.
In addition, the electronic device further includes: a display 808 for displaying the target quantization factor; and a connection bus 810 for connecting the respective module parts in the above-described electronic apparatus.
In other embodiments, the terminal device or the server may be a node in a distributed system, where the distributed system may be a blockchain system, and the blockchain system may be a distributed system formed by connecting a plurality of nodes through a network communication. Nodes can form a Peer-To-Peer (P2P, Peer To Peer) network, and any type of computing device, such as a server, a terminal, and other electronic devices, can become a node in the blockchain system by joining the Peer-To-Peer network.
According to an aspect of the application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. A processor of the computer device reads the computer instructions from the computer-readable storage medium, the processor executing the computer instructions to cause the computer device to perform the above rate-distortion optimized quantization method, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the above-mentioned computer-readable storage medium may be configured to store a computer program for executing the steps of:
s1, dividing all minimum subunits of the conversion units in the video frame to obtain a conversion subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits;
s2, determining a representative value of the quantized coefficients of each of the transform sub-units;
s3, based on the representative value, calculating the first code rate distortion cost corresponding to the transformation unit when each transformation subunit is used as the last non-zero coefficient unit of zigzag scanning;
s4, taking the transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set;
and S5, outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
Alternatively, in this embodiment, a person skilled in the art may understand that all or part of the steps in the methods of the foregoing embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be substantially or partially implemented in the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, and including instructions for causing one or more computer devices (which may be personal computers, servers, or network devices) to execute all or part of the steps of the method according to the embodiments of the present invention.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that it is obvious to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and these modifications and improvements should also be considered as the protection scope of the present invention.
Claims (10)
1. A rate-distortion optimized quantization method, comprising:
dividing all minimum subunits of a transformation unit in a video frame to obtain a transformation subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits;
determining a representative value of the quantized coefficients of each transform sub-unit;
based on the representative value, sequentially calculating a first code rate distortion cost corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of the zigzag scanning;
taking a transformation subunit set corresponding to the zigzag scanning with the minimum first code rate distortion cost as a target transformation subunit set;
and outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
2. The method of claim 1, wherein determining the representative value of the quantized coefficients of each transform sub-unit comprises:
and taking the average value of the quantized coefficients of all the minimum sub-units in each transformation sub-unit as the representative value.
3. The method according to claim 1, wherein the first rate distortion cost corresponding to each transform subunit is obtained by the following formula when each transform subunit is used as the last non-zero coefficient unit of the zigzag scan:
Jj,coded＝Dcoded,j+λ·Rcoded,j； (2)
Jj,uncoded＝Duncoded,j+λ·Runcoded,j； (3)
wherein, Ji,islastRepresenting the first rate distortion cost, J, of the current transform subunit as the last non-zero coefficient unitj,codedRepresenting the rate distortion cost, J, required to encode the quantized coefficients of the current transform subunitj,uncodedRepresenting the rate-distortion cost, D, required to truncate the quantized coefficientscoded,j，Duncoded,jRespectively correspondingly coding the current quantization coefficient and eliminating the distortion parameter of the current quantization coefficient; r iscoded,j，Runcoded,jAnd respectively correspondingly coding the current quantization coefficient and truncating the code rate of the current quantization coefficient, wherein lambda is a Lagrange coefficient.
4. The method of claim 1, wherein before the dividing all minimum sub-units of a transform unit in a video frame into a set of transform sub-units, the method comprises:
acquiring an initial quantization coefficient corresponding to each minimum subunit of a transformation unit;
processing the initial quantization coefficients by a formula (4) to obtain preprocessed quantization coefficients corresponding to each initial quantization coefficient:
wherein PQCoeff is a preprocessed quantized coefficient, TransCoeff is an initial quantized coefficient, Round is a rounding operation function, and Qstep is a quantization step size;
and obtaining the quantized coefficient of each minimum subunit based on the preprocessed quantized coefficients.
5. The method according to claim 4, wherein said obtaining the quantized coefficients of each minimum sub-unit based on the preprocessed quantized coefficients comprises:
aiming at each minimum subunit, respectively calculating a second code rate distortion cost required by a preprocessing quantization coefficient, a first reference quantization coefficient and a second reference quantization coefficient corresponding to each minimum subunit;
and taking the value with the minimum second code rate distortion cost as the quantization coefficient of the current minimum subunit.
6. The method of claim 1, further comprising:
and outputting the scanning position information corresponding to each minimum subunit in the target transformation subunit set.
7. A rate-distortion optimized quantization apparatus, comprising:
the dividing unit is used for dividing all the minimum subunits of the conversion unit in the video frame to obtain a conversion subunit set; wherein each transform subunit in the set of transform subunits comprises a plurality of the minimum subunits;
a first determining unit for determining a representative value of the quantized coefficients of each of the transform sub-units;
the calculation unit is used for sequentially calculating the distortion cost of a first code rate corresponding to each transformation subunit when each transformation subunit is used as the last non-zero coefficient unit of the zigzag scanning based on the representative value;
the second determining unit is used for taking a transformation subunit set corresponding to the Z-shaped scanning with the minimum first code rate distortion cost as a target transformation subunit set;
and the first output unit is used for outputting the target quantization coefficient corresponding to each minimum subunit in the target transformation subunit set.
8. The apparatus according to claim 7, wherein the first determining unit specifically includes:
a first determining module, configured to use an average value of the quantized coefficients of all the smallest sub-units in each transform sub-unit as the representative value.
9. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 6 by means of the computer program.
10. A computer-readable storage medium, comprising a stored program, wherein the program when executed performs the method of any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210225735.9A CN114786010A (en) | 2022-03-07 | 2022-03-07 | Rate distortion optimization quantization method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210225735.9A CN114786010A (en) | 2022-03-07 | 2022-03-07 | Rate distortion optimization quantization method and device, storage medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114786010A true CN114786010A (en) | 2022-07-22 |
Family
ID=82423457
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210225735.9A Pending CN114786010A (en) | 2022-03-07 | 2022-03-07 | Rate distortion optimization quantization method and device, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114786010A (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080279466A1 (en) * | 2007-05-08 | 2008-11-13 | Kyeong Ho Yang | Methods and Systems for Rate-Distortion Optimized Quantization of Transform Blocks in Block Transform Video Coding |
| CA2732218A1 (en) * | 2010-02-18 | 2011-08-18 | Research In Motion Limited | Method and encoder for constrained soft-decision quantization in data compression |
| CN102651816A (en) * | 2011-02-23 | 2012-08-29 | 华为技术有限公司 | Method and device for scanning transformation coefficient block |
| CN104221375A (en) * | 2012-04-13 | 2014-12-17 | 高通股份有限公司 | Level decision in rate distortion optimized quantization |
| CN111556313A (en) * | 2020-04-26 | 2020-08-18 | 武汉理工大学 | Low-complexity DTT (dynamic time warping) and self-adaptive quantization image compression method based on integer approximation |
| CN111787324A (en) * | 2020-06-29 | 2020-10-16 | 北京大学 | Method for rate distortion optimization quantization, encoding method and device |
| CN113259667A (en) * | 2021-05-17 | 2021-08-13 | 北京百度网讯科技有限公司 | Video quantization method, video quantization device, electronic equipment and computer-readable storage medium |
| CN113422957A (en) * | 2021-05-17 | 2021-09-21 | 北京百度网讯科技有限公司 | Quantization method, apparatus, device and storage medium in video coding |
| CN113489978A (en) * | 2021-05-27 | 2021-10-08 | 杭州博雅鸿图视频技术有限公司 | Distortion optimization quantization circuit for AVS3 |
| CN113573056A (en) * | 2021-05-25 | 2021-10-29 | 杭州博雅鸿图视频技术有限公司 | Method, device, storage medium and terminal for optimizing and quantizing rate distortion |
| WO2022021422A1 (en) * | 2020-07-31 | 2022-02-03 | Oppo广东移动通信有限公司 | Video coding method and system, coder, and computer storage medium |
-
2022
- 2022-03-07 CN CN202210225735.9A patent/CN114786010A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080279466A1 (en) * | 2007-05-08 | 2008-11-13 | Kyeong Ho Yang | Methods and Systems for Rate-Distortion Optimized Quantization of Transform Blocks in Block Transform Video Coding |
| CA2732218A1 (en) * | 2010-02-18 | 2011-08-18 | Research In Motion Limited | Method and encoder for constrained soft-decision quantization in data compression |
| CN102651816A (en) * | 2011-02-23 | 2012-08-29 | 华为技术有限公司 | Method and device for scanning transformation coefficient block |
| CN104221375A (en) * | 2012-04-13 | 2014-12-17 | 高通股份有限公司 | Level decision in rate distortion optimized quantization |
| CN111556313A (en) * | 2020-04-26 | 2020-08-18 | 武汉理工大学 | Low-complexity DTT (dynamic time warping) and self-adaptive quantization image compression method based on integer approximation |
| CN111787324A (en) * | 2020-06-29 | 2020-10-16 | 北京大学 | Method for rate distortion optimization quantization, encoding method and device |
| WO2022021422A1 (en) * | 2020-07-31 | 2022-02-03 | Oppo广东移动通信有限公司 | Video coding method and system, coder, and computer storage medium |
| CN113259667A (en) * | 2021-05-17 | 2021-08-13 | 北京百度网讯科技有限公司 | Video quantization method, video quantization device, electronic equipment and computer-readable storage medium |
| CN113422957A (en) * | 2021-05-17 | 2021-09-21 | 北京百度网讯科技有限公司 | Quantization method, apparatus, device and storage medium in video coding |
| CN113573056A (en) * | 2021-05-25 | 2021-10-29 | 杭州博雅鸿图视频技术有限公司 | Method, device, storage medium and terminal for optimizing and quantizing rate distortion |
| CN113489978A (en) * | 2021-05-27 | 2021-10-08 | 杭州博雅鸿图视频技术有限公司 | Distortion optimization quantization circuit for AVS3 |
Non-Patent Citations (5)
| Title |
|---|
| 向国庆等: "A novel RDO based on perceptual algorithm", 2020 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE), 23 April 2020 (2020-04-23) * |
| 向国庆等: "An improved adaptive quantization method based on perceptual CU early splitting for HEVC", 2017 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE), 10 January 2017 (2017-01-10) * |
| 李娜娜;黄琨强;张秋闻;刘宽;: "基于自适应量化器选择的编码率失真优化判决算法", 郑州大学学报(工学版), no. 03 * |
| 李娜娜;黄琨强;张秋闻;刘宽;: "基于自适应量化器选择的编码率失真优化判决算法", 郑州大学学报(工学版), no. 03, 5 January 2019 (2019-01-05) * |
| 贾川民等: "视频处理与压缩技术", 中国图象图形学报, 30 June 2021 (2021-06-30) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP2021520082A (en) | Use of nonlinear functions applied to the quantization parameters of machine learning models for video coding | |
| CN105100814B (en) | Image coding and decoding method and device | |
| WO2019045798A1 (en) | Selective mixing of probability distributions for entropy coding in video compression | |
| CN110870310A (en) | Image encoding method and apparatus | |
| CN108600783B (en) | Frame rate adjusting method and device and terminal equipment | |
| US20220076380A1 (en) | Method of controlling encoding of display data | |
| CN112104867B (en) | Video processing method, video processing device, intelligent equipment and storage medium | |
| US20230281881A1 (en) | Video Frame Compression Method, Video Frame Decompression Method, and Apparatus | |
| CN110740324B (en) | Coding control method and related device | |
| CN114786010A (en) | Rate distortion optimization quantization method and device, storage medium and electronic equipment | |
| CN115442617A (en) | Video processing method and device based on video coding | |
| CN114374841A (en) | Optimization method and device for video coding rate control and electronic equipment | |
| CN113435515A (en) | Picture identification method and device, storage medium and electronic equipment | |
| CN114827583A (en) | System and method for objective video quality assessment in lightweight real-time video communication | |
| CN112509107A (en) | Point cloud attribute recoloring method, device and encoder | |
| CN105306941A (en) | Video coding method | |
| CN113365016A (en) | Real-time map image data acquisition system and method | |
| Kim et al. | Implementation of DWT-based adaptive mode selection for LCD overdrive | |
| CN114501015B (en) | Video coding rate processing method and device, storage medium and electronic equipment | |
| CN114827289B (en) | Communication compression method, system, electronic device and storage medium | |
| CN111260051B (en) | Neural network operation method and related device | |
| CN112261443B (en) | Image processing method and device and image processing system | |
| EP4117289A1 (en) | Image processing method and image processing device | |
| US11670008B2 (en) | Processing display data for transmission | |
| WO2022140937A1 (en) | Point cloud encoding method and system, point cloud decoding method and system, point cloud encoder, and point cloud decoder |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |