CN108900838A - A kind of Rate-distortion optimization method based on HDR-VDP-2 distortion criterion - Google Patents
A kind of Rate-distortion optimization method based on HDR-VDP-2 distortion criterion Download PDFInfo
- Publication number
- CN108900838A CN108900838A CN201810586755.2A CN201810586755A CN108900838A CN 108900838 A CN108900838 A CN 108900838A CN 201810586755 A CN201810586755 A CN 201810586755A CN 108900838 A CN108900838 A CN 108900838A
- Authority
- CN
- China
- Prior art keywords
- hdr
- distortion
- rate
- coding
- value
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000005457 optimization Methods 0.000 title claims abstract description 13
- 238000013139 quantization Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000009795 derivation Methods 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 2
- 238000005259 measurement Methods 0.000 abstract 1
- 230000006870 function Effects 0.000 description 30
- 238000012360 testing method Methods 0.000 description 9
- 230000005540 biological transmission Effects 0.000 description 6
- 230000008447 perception Effects 0.000 description 5
- 230000000873 masking effect Effects 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000005622 photoelectricity Effects 0.000 description 1
- 238000013441 quality evaluation Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
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
- H04N19/134—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
- H04N19/134—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
- H04N19/154—Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion
-
- 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
- H04N19/186—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 colour or a chrominance component
-
- 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
- H04N19/189—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding
- H04N19/19—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding using optimisation based on Lagrange multipliers
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
Abstract
The present invention relates to a kind of Rate-distortion optimization methods based on HDR-VDP-2 measurement distortion, and Lagrange multiplier λ is corrected according to revised λ-QP relationship, to advanced optimize the Selection Strategy of coding parameter in HDR video coding process, the performance that HEVC Main 10 encodes HDR video is improved.Firstly, devising a kind of distortion computation method based on HDR-VDP-2 and the coding tree unit structure applied to HEVC, and establish the rate distortion costs function model based on HDR-VDP-2 distortion criterion;Then, in order to determine the Lagrange multiplier λ in rate distortion costs function, the present invention is encoded using fixed Lagrange multiplier λ, and counts optimal QP value using more QP optimisation techniques, to correct λ-QP functional relation;Finally, determining the Lagrange multiplier λ of present encoding video frame based on the relationship between amendment λ-QP, and the rate distortion costs function model of proposition is applied to 10 encoder of HEVC Main.Meanwhile the present invention can retain the more texture detail informations of coding and rebuilding video, be able to ascend HEVC coding HDR video performance.
Description
Technical field
The present invention relates to HDR technical field of video coding, more particularly, to a kind of rate based on HDR-VDP-2 distortion criterion
Distortion optimizing method.
Background technique
In reality scene, the distribution of true brightness value is very wide:In the case where direct sunlight, scene brightness is reachable
To 105cd/m2, and shady place brightness value may only have 10-3cd/m2.High dynamic range (High Dynamic Range, HDR) figure
As comparing with common low dynamic (Low Dynamic Range, LDR) image, HDR image dynamic range is bigger, HDR image institute energy
The level of performance is more abundant, to reach the effect of shadow for more approaching reality.However, current newest video encoding standard
HEVC (High Efficiency Video Coding) is for LDR video designs, with locating depth and dynamic range
Increase, this also proposes new challenge to HDR Video coding, therefore HDR Video coding becomes current HDR Video coding transmission
Key technology urgently to be solved.
Existing HDR method for video coding can be classified as two classes:The HDR Video coding of back compatible is converted based on perception
The non-back compatible HDR Video coding of function.The HDR Video coding of back compatible can be compatible with existing 8 LDR Video codings
Transmission and display equipment, can directly decode the code stream of Primary layer in decoding end, for intercepting HDR tone mapping operation (Tone-
Mapping Operator, TMO) after LDR content.Equally it can also pass through Primary layer by decoding whole code stream informations
The residual information of LDR content and enhancement layer decoding display HDR content.Although this coding mode can be traditional with compatible transmission
LDR video, but the mode being classified increases encoder bit rate while also to transmission bandwidth, more stringent requirements are proposed.
Another kind of is the coding mode of the non-back compatible based on perception transfer function:Using based on human visual system
Perception transfer function (the Perceptual Transformation of (Human Visual System, HVS) sensor model
Function, PTF), integer data storage format needed for the HDR data of floating type are transformed into coding transmission finally utilizes
The video encoder of 10 or higher locating depth is compressed.The purpose of PTF is in order to use coding locating depth few as far as possible, to indicate
HDR image content.Miller et al. is based on Contrast sensitivity function (Contrast Sensitivity Function, CSF) and builds
Perception quantization (Perceptual Quantizer, PQ) model has been found, has made photoelectricity on the basis of compatible existing REC.709 standard
Transfer function is smooth, keeps HDR content information and perceived quality to greatest extent limiting in locating depth limitation.Jung et al. is based on
CSF model obtains the adaption brightness adjusting method of 10 bits, and improves the FEJND model of LDR, compiles for optimizing HDR video
Lagrange multiplier in code device.Zhang et al. optimizes LDR image brightness masking model based on the brightness masking characteristics of HDR, with
It obtains the brightness masking function of HDR image and perceives and adjust quantization parameter removal perception redundancy.
Although relevant research all improves code efficiency to a certain extent, there is no solve high performance video to compile
In code (High EfficiencyVideo Coding, HEVC) traditional rate distortion metrics can not sound response HDR image coding
The problem of distortion level.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of distortion performances that can be improved HDR Video coding, and
And optimize the rate-distortion optimization side based on HDR-VDP-2 distortion criterion of coding parameter Selection Strategy in HDR video coding process
Method.
The technical scheme adopted by the invention is that a kind of Rate-distortion optimization method based on HDR-VDP-2 distortion criterion, packet
Include following steps:
(1), distortion computation is carried out to the current coded unit (CodingUnit, CU) based on HDR-VDP-2 distortion criterion:
CU after rebuilding first to present encoding calculates the evaluation index P of its HDR-VDP-2map, and using to PmapSeek the side of 1 norm
Formula measures the distortion level D of the image block of current CUHDR, i.e. DHDR=| | Pmap||1;Wherein PmapEach of middle current CU of correspondence
Pixel has an a possibility that probability value, the bigger expression pixel of the value perceives distortion difference bigger, then the picture
Vegetarian refreshments distortion level is also bigger, PmapIt is expressed as:
Wherein Ψ is that can operate Pyramid Reconstruction, β
It is 3.5 for its exponential constant value;
(2), the Lagrange multiplier λ of video frame where determining current coded unit CU:Again by rate distortion costs function
It is defined as J=DHDR+ λ R, coding bit rate needed for wherein R indicates current CU coding, λ are used by present encoding video frame
Lagrange multiplier;Then, the functional relation between λ and quantization parameter (Quantization Parameter, QP) is obtained,
It can be expressed as by converting obtained functional relationNext, seeking dR/ respectively
DQP and dDHDRThe function model of/dQP;Subsequently, the distribution situation of QP and λ are obtained by data statistics, and use functional relationIt is fitted and assesses the functional relation of QP and λ, so that it is determined that phase in λ-QP function out
Close the value of parameter;Finally, determining present encoding according to revised λ-QP function when encoder is using fixed QP value quantization
Lagrange multiplier λ used by video frame, wherein Lagrange multiplier λ is for balanced code rate R and distortion DHDR;
(3), rate distortion costs function is calculated:After the Lagrange multiplier λ of video frame is determined where current CU, pass through HEVC
10 encoder of Main carries out HDR Video coding;Firstly, defining the rate distortion costs function J=of the CU after present encoding is rebuild
DHDR+λ·R;Then, it is encoded for the luminance component of current CU, the different depth of different prediction modes, CU is divided
And other coding parameters choose process and carry out calculating rate distortion costs value according to the rate distortion costs function redefined,
And choose rate distortion costs and be worth the smallest coding parameter as the coding parameter finally encoded, and for the chromatic component of current CU
It is still calculated according to the rate distortion costs calculation of 10 encoder of HEVC Main when calculating rate distortion costs value.
The beneficial effects of the present invention are embodied in these three aspects:
The first, the method for the present invention is in order to the distortion interpretational criteria based on HDR-VDP-2 to be more easily and fast applied to
The distortion that CU is calculated in HEVC, uses probability matrix P identical with distortion computation tile sizemap, and seek 1 norm
Mode measures the distortion level of current CU image block, proposes a kind of rate distortion costs calculation method based on HDR-VDP-2.
The second, the method for the present invention derives λ-QP relational model and modified Lagrange multiplier λ according to statistical data, with into
The Selection Strategy of coding parameter in one-step optimization HDR video coding process, can retain the more grain details of coding and rebuilding video
Information, to improve the distortion performance of HDR Video coding.
Third, the method for the present invention are for the HDR video encoding rate distortion proposed on the basis of 10 encoder of HEVC Main
Optimization method, therefore existing 10 digital video coding transmission software and hardware basis can be made full use of to set in actual coding HDR video
It applies.
As preferential, in above-mentioned steps (2), the Lagrange multiplier λ of video frame where determining current coded unit CU
The specific steps are:
A, rate distortion costs function is newly defined as J=DHDR+ λ R, coding needed for wherein R indicates current CU coding
Bit rate, λ are Lagrange multiplier used by present encoding video frame;
B, rate distortion costs function is minimized, by rate distortion costs calculation formula J=DHDR+ λ R both members are right respectively
Code rate R derivation, and enable it equal to 0, the functional relation being translated between λ and QP, i.e.,
C, dR/dQP and dD then, are sought respectivelyHDR/ dQP function model;
D, the relationship that both quantization step Q and QP are got in HEVC is:R (Q)=τ 2(QP-4)α/6, wherein τ and α are
Constant relevant to source signal;
E, distortion level DHDRThere are statistical relationship ln (D between QPHDR)=aQP+b counts the average distortion D of CUHDR
0.2443 and -4.42 are taken respectively with the value of a and b in the distribution situation and determination statistical relationship of QP, and are obtained Lagrange and multiplied
The function model of sub- λ and QPWherein, Φ=(6 × 22α/3)/
(ln2 × τ α), γ=2-α/6, the two parameters of Φ and γ are constants relevant to source signal in model;
F, fixed λ and the encoded video by the way of more QP optimization, and count the appearance frequency corresponding to CU under fixed λ value
Secondary highest QP uses function model as optimal QPFitting
And the functional relation of optimal QP and λ are assessed, so that it is determined that the value of parameter Φ and γ;
G, finally, being calculated according to revised λ-QP function and QP value current when encoder is using fixed QP value quantization
Lagrange multiplier λ used by encoded video frame.
λ-QP relational model and modified Lagrange multiplier λ are derived according to statistical data, can optimize HDR Video coding
The Selection Strategy of coding parameter in the process, and improve the distortion performance of HDR Video coding.
Detailed description of the invention
Fig. 1 is the overall block flow diagram of the method for the present invention;
Fig. 2 is that the method for the present invention and other methods put the 1st frame image coding and rebuilding image of Market3 sequence and part
Big figure compares.
Specific embodiment
It is invented referring to the drawings and in conjunction with specific embodiment to further describe, to enable those skilled in the art's reference
Specification word can be implemented accordingly, and the scope of the present invention is not limited to the specific embodiment.
The present invention relates to a kind of Rate-distortion optimization methods based on HDR-VDP-2 distortion criterion, include the following steps:
(1), to current based on HDR-visible difference predictor-2 (HDR-VDP-2) distortion criterion
Coding unit (CodingUnit, CU) carries out distortion computation:CU after rebuilding first to present encoding calculates its HDR-VDP-2's
Evaluation index Pmap, and using to PmapSeek 1 norm mode measure current CU image block distortion level DHDR, i.e. DHDR=
||Pmap||1;Each pixel in current CU is wherein corresponded in Pmap a probability value, the bigger expression pixel of the value
It is bigger that point perceives a possibility that distortion difference, then the pixel distortion level is also bigger, PmapIt is expressed as:
Wherein Ψ is that can operate Pyramid Reconstruction, β
It is 3.5 for its exponential constant value;
(2), the Lagrange multiplier λ of video frame where determining current coded unit CU:
A, rate distortion costs function is newly defined as J=DHDR+ λ R, coding needed for wherein R indicates current CU coding
Bit rate, λ are Lagrange multiplier used by present encoding video frame;
B, rate distortion costs function is minimized, by rate distortion costs calculation formula J=DHDR+ λ R both members are right respectively
Code rate R derivation, and enable it equal to 0, the functional relation being translated between λ and QP, i.e.,
C, dR/dQP and dD then, are sought respectivelyHDR/ dQP function model;
D, the relationship that both quantization step Q and QP are got in HEVC is:R (Q)=τ 2(QP-4)α/6, wherein τ and α are
Constant relevant to source signal;
E, distortion level DHDRThere are statistical relationship ln (D between QPHDR)=aQP+b counts the average distortion D of CUHDR
0.2443 and -4.42 are taken respectively with the value of a and b in the distribution situation and determination statistical relationship of QP, and are obtained Lagrange and multiplied
The function model of sub- λ and QPWherein, Φ=(6 × 22α/3)/
(ln2 × τ α), γ=2-α/6, the two parameters of Φ and γ are constants relevant to source signal in model;
F, fixed λ and the encoded video by the way of more QP optimization, and count the appearance frequency corresponding to CU under fixed λ value
Secondary highest QP uses function model as optimal QPFitting
And the functional relation of optimal QP and λ are assessed, so that it is determined that the value of parameter Φ and γ;
G, finally, being calculated according to revised λ-QP function and QP value current when encoder is using fixed QP value quantization
Lagrange multiplier λ used by encoded video frame.
(4), rate distortion costs function is calculated:After the Lagrange multiplier λ of video frame is determined where current CU, pass through HEVC
10 encoder of Main carries out HDR Video coding;Firstly, defining the rate distortion costs function J=of the CU after present encoding is rebuild
DHDR+λ·R;Then, it is encoded for the luminance component of current CU, the different depth of different prediction modes, CU is divided
And other coding parameters choose process and carry out calculating rate distortion costs value according to the rate distortion costs function redefined,
And choose rate distortion costs and be worth the smallest coding parameter as the coding parameter finally encoded, and for the chromatic component of current CU
It is still calculated according to the rate distortion costs calculation of 10 encoder of HEVC Main when calculating rate distortion costs value.
For the feasibility and validity for further illustrating foregoing invention method, tested as follows.
Experiment uses Market3, BalloonFestival, Hurdles and Sunrise cycle tests, resolution ratio 1920
× 1080, and saved with OpenEXR format.By Sequence Transformed for sample format 4 before coding:2:0 YCbCr format text
The frame per second of part, FireEater and SunRise are 25fps, and the frame per second of Market, Hurdles are 50fps.
It is complete in the reference test platform HM 16.9Main10Profile of HEVC in order to test the reasonability of proposed model
It is tested in (All Intra, AI) configuration in frame.The QP for testing the fixation used is set as { 22,27,32,37 }, and with
The HDR Video Coding Scheme of HEVC Main 10 compares the variation percentage of code rate, and final encoding efficiency is come using BD-rate
The distortion performance of measure algorithm, wherein the meaning of BD-rate is encoder bit rate changes under equivalent video quality score value hundred
Divide ratio.And calculate the HDR-VDP-2 quality evaluation score value of final encoded video frame to measure video objective quality, wherein HDR-
The prediction score value Q of VDP-2MOSBigger reaction picture quality is better.
The BD-rate gain (%) that each cycle tests of table 1 uses the method for the present invention to be encoded
The method of the present invention its BD-rate gain compared with reference to test platform HM 16.9Main10, and use HDR-VDP-
The final coding distortion degree of 2 assessments.Table 1 lists BD-rate of the method for the present invention under different cycle tests as a result, from reality
Test data can be seen that the method for the present invention compared with HM 16.9 under identical encoder bit rate have higher QMOSValue, and BD-
Rate result is better than comparison algorithm.Due to QMOSWhat value indicated is the subjective perceptual quality of assessment, and the method proposed is in same code
Video encoding quality is improved under rate, binary encoding performance is better than original test platform HM 16.9.In same HDR-VDP-2 visitor
In the case of appearance quality, code rate changes from -1.27% to -19.01% range of percentage, and mean coding gain improves
7.78%.Wherein for BalloonFestival sequence under same HDR-VDP-2 mass, coding gain has reached 19.01%,
There has also been different degrees of promotions for his sequential coding effect.
Claims (2)
1. a kind of Rate-distortion optimization method based on HDR-VDP-2 distortion criterion, it is characterised in that:Include the following steps:
(1), distortion computation is carried out to the current CU based on HDR-VDP-2 distortion criterion:CU after being rebuild first to present encoding
Calculate the evaluation index P of its HDR-VDP-2map, and using to PmapSeek 1 norm mode measure current CU image block mistake
True degree DHDR, i.e. DHDR=| | Pmap||1;Wherein PmapEach pixel in the middle current CU of correspondence has a probability value, should
It is bigger to be worth a possibility that bigger expression pixel perceives distortion difference, then the pixel distortion level is also bigger, PmapTable
It is shown as:Wherein Ψ is that can operate Pyramid Reconstruction, and β is it
Exponential constant value is 3.5;
(2), the Lagrange multiplier λ of video frame where determining current CU:Rate distortion costs function is newly defined as J=DHDR+
λ R, coding bit rate needed for wherein R indicates current CU coding, λ are that Lagrange used by present encoding video frame multiplies
Son;Then, the functional relation between λ and QP is obtained, is expressed as by the functional relation obtained after conversionNext, seeking dR/dQP and dD respectivelyHDRThe function model of/dQP;Subsequently, lead to
Data statistics is crossed to obtain the distribution situation of QP and λ, and uses functional relationTo be fitted simultaneously
Assess QP and λ functional relation, so that it is determined that out in λ-QP function relevant parameter value;Finally, when encoder is using fixation
When QP value quantifies, Lagrange multiplier λ used by determining present encoding video frame according to revised λ-QP function, the glug
Bright day multiplier λ is for balanced code rate R and distortion DHDR;
(3), rate distortion costs function is calculated:After the Lagrange multiplier λ of video frame is determined where current CU, pass through HEVC
10 encoder of Main carries out HDR Video coding;Firstly, defining the rate distortion costs function J=of the CU after present encoding is rebuild
DHDR+λ·R;Then, it is encoded for the luminance component of current CU, the different depth of different prediction modes, CU is divided
And other coding parameters choose process and carry out calculating rate distortion costs value according to the rate distortion costs function redefined,
And choose rate distortion costs and be worth the smallest coding parameter as the coding parameter finally encoded, and for the chromatic component of current CU
It is still calculated according to the rate distortion costs calculation of 10 encoder of HEVC Main when calculating rate distortion costs value.
2. a kind of Rate-distortion optimization method based on HDR-VDP-2 distortion criterion according to claim 1, feature exist
In:In above-mentioned steps (2), the Lagrange multiplier λ of video frame where determining current coded unit CU the specific steps are:
A, rate distortion costs function is newly defined as J=DHDR+ λ R, coded-bit needed for wherein R indicates current CU coding
Rate, λ are Lagrange multiplier used by present encoding video frame;
B, rate distortion costs function is minimized, by rate distortion costs calculation formula J=DHDR+ λ R both members are respectively to code rate R
Derivation, and enable it equal to 0, the functional relation being translated between λ and QP, i.e.,
C, dR/dQP and dD then, are sought respectivelyHDR/ dQP function model;
D, the relationship that both quantization step Q and QP are got in HEVC is:R (Q)=τ 2(QP-4)α/6, wherein τ and α be and letter
The relevant constant of source signal;
E, distortion level DHDRThere are statistical relationship ln (D between QPHDR)=aQP+b counts the average distortion D of CUHDRAnd QP
Distribution situation and determine that the value of a and b takes 0.2443 and -4.42 respectively in statistical relationship, and obtain Lagrange multiplier λ and
The function model of QPWherein, Φ=(6 × 22α/3)/(ln2
× τ α), γ=2-α/6, the two parameters of Φ and γ are constants relevant to source signal in model;
F, fixed λ and using encoded video by the way of more QP optimization, and count under fixation λ value frequency of occurrence corresponding to CU most
High QP uses function model as optimal QPIt is fitted and comments
The functional relation of optimal QP and λ are estimated, so that it is determined that the value of parameter Φ and γ;
G, finally, calculating present encoding according to revised λ-QP function and QP value when encoder is using fixed QP value quantization
Lagrange multiplier λ used by video frame.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810586755.2A CN108900838B (en) | 2018-06-08 | 2018-06-08 | Rate distortion optimization method based on HDR-VDP-2 distortion criterion |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810586755.2A CN108900838B (en) | 2018-06-08 | 2018-06-08 | Rate distortion optimization method based on HDR-VDP-2 distortion criterion |
Publications (2)
Publication Number | Publication Date |
---|---|
CN108900838A true CN108900838A (en) | 2018-11-27 |
CN108900838B CN108900838B (en) | 2021-10-15 |
Family
ID=64344321
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810586755.2A Active CN108900838B (en) | 2018-06-08 | 2018-06-08 | Rate distortion optimization method based on HDR-VDP-2 distortion criterion |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108900838B (en) |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112437301A (en) * | 2020-10-13 | 2021-03-02 | 北京大学 | Code rate control method and device for visual analysis, storage medium and terminal |
WO2021120614A1 (en) * | 2019-12-16 | 2021-06-24 | 电子科技大学 | Secondary coding optimization method |
CN113784130A (en) * | 2021-08-09 | 2021-12-10 | 西安交通大学 | Bit allocation method based on gradient mode similarity dispersion minimization |
CN114868386A (en) * | 2020-12-03 | 2022-08-05 | Oppo广东移动通信有限公司 | Encoding method, decoding method, encoder, decoder, and electronic device |
CN115428451A (en) * | 2020-07-31 | 2022-12-02 | Oppo广东移动通信有限公司 | Video encoding method, encoder, system, and computer storage medium |
CN117440158A (en) * | 2023-12-20 | 2024-01-23 | 华侨大学 | MIV immersion type video coding rate distortion optimization method based on three-dimensional geometric distortion |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140119432A1 (en) * | 2011-06-14 | 2014-05-01 | Zhou Wang | Method and system for structural similarity based rate-distortion optimization for perceptual video coding |
CN104054338A (en) * | 2011-03-10 | 2014-09-17 | 杜比实验室特许公司 | Bitdepth And Color Scalable Video Coding |
WO2015128295A1 (en) * | 2014-02-26 | 2015-09-03 | Thomson Licensing | Method and apparatus for encoding and decoding hdr images |
CN105812805A (en) * | 2016-01-31 | 2016-07-27 | 西安电子科技大学 | Coding method and apparatus for video images |
CN106303521A (en) * | 2016-08-15 | 2017-01-04 | 华侨大学 | A kind of HEVC Rate-distortion optimization method based on sensitivity of awareness |
CN107079154A (en) * | 2014-11-05 | 2017-08-18 | 苹果公司 | The HDR video multi-tiered compression technologies of back compatible |
-
2018
- 2018-06-08 CN CN201810586755.2A patent/CN108900838B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104054338A (en) * | 2011-03-10 | 2014-09-17 | 杜比实验室特许公司 | Bitdepth And Color Scalable Video Coding |
US20140119432A1 (en) * | 2011-06-14 | 2014-05-01 | Zhou Wang | Method and system for structural similarity based rate-distortion optimization for perceptual video coding |
WO2015128295A1 (en) * | 2014-02-26 | 2015-09-03 | Thomson Licensing | Method and apparatus for encoding and decoding hdr images |
CN107079154A (en) * | 2014-11-05 | 2017-08-18 | 苹果公司 | The HDR video multi-tiered compression technologies of back compatible |
CN105812805A (en) * | 2016-01-31 | 2016-07-27 | 西安电子科技大学 | Coding method and apparatus for video images |
CN106303521A (en) * | 2016-08-15 | 2017-01-04 | 华侨大学 | A kind of HEVC Rate-distortion optimization method based on sensitivity of awareness |
Non-Patent Citations (2)
Title |
---|
RAFAL MANTIUK等: "HDR-VDP-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions", 《ACM TRANSACTIONS ON GRAPHICS》 * |
朱天之等: "基于SSIM的HEVC帧内编码率失真优化", 《光电子·激光》 * |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2021120614A1 (en) * | 2019-12-16 | 2021-06-24 | 电子科技大学 | Secondary coding optimization method |
CN115428451A (en) * | 2020-07-31 | 2022-12-02 | Oppo广东移动通信有限公司 | Video encoding method, encoder, system, and computer storage medium |
CN112437301A (en) * | 2020-10-13 | 2021-03-02 | 北京大学 | Code rate control method and device for visual analysis, storage medium and terminal |
CN114868386A (en) * | 2020-12-03 | 2022-08-05 | Oppo广东移动通信有限公司 | Encoding method, decoding method, encoder, decoder, and electronic device |
CN114868386B (en) * | 2020-12-03 | 2024-05-28 | Oppo广东移动通信有限公司 | Encoding method, decoding method, encoder, decoder, and electronic device |
CN113784130A (en) * | 2021-08-09 | 2021-12-10 | 西安交通大学 | Bit allocation method based on gradient mode similarity dispersion minimization |
CN113784130B (en) * | 2021-08-09 | 2024-05-07 | 西安交通大学 | Bit allocation method based on gradient mode similarity dispersion minimization |
CN117440158A (en) * | 2023-12-20 | 2024-01-23 | 华侨大学 | MIV immersion type video coding rate distortion optimization method based on three-dimensional geometric distortion |
CN117440158B (en) * | 2023-12-20 | 2024-04-12 | 华侨大学 | MIV immersion type video coding rate distortion optimization method based on three-dimensional geometric distortion |
Also Published As
Publication number | Publication date |
---|---|
CN108900838B (en) | 2021-10-15 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108900838A (en) | A kind of Rate-distortion optimization method based on HDR-VDP-2 distortion criterion | |
US11727548B2 (en) | Method and apparatus for encoding and decoding HDR images | |
RU2644065C1 (en) | Decomposition of levels in hierarchical vdr encoding | |
RU2666234C1 (en) | Approximation of signal waveform recovery | |
KR101794817B1 (en) | Encoding and decoding perceptually-quantized video content | |
CN108769677B (en) | High dynamic range video dynamic range scalable coding method based on perception | |
US20200068200A1 (en) | Methods and apparatuses for encoding and decoding video based on perceptual metric classification | |
CN1285115A (en) | Apparatus and method for object based rate control in coding system | |
US10778983B2 (en) | Preserving texture/noise consistency in video codecs | |
JP2015501604A (en) | Perceptually lossless and perceptually enhanced image compression system and method | |
CN107211145A (en) | The almost video recompression of virtually lossless | |
US11025914B1 (en) | Method based on global rate-distortion optimization for rate control in video coding | |
CN1157079A (en) | Device and method for coding video pictures | |
CN106063266A (en) | Method and apparatus for encoding image data and method and apparatus for decoding image data | |
CN108574841A (en) | A kind of coding method and device based on adaptive quantizing parameter | |
US20230232016A1 (en) | Point cloud encoding method and related apparatuses | |
EP3913917A1 (en) | Methods for performing encoding and decoding, decoding end and encoding end | |
CN101472182B (en) | Virtually lossless video data compression | |
CN112040231B (en) | Video coding method based on perceptual noise channel model | |
CN107820084B (en) | Video perception coding method and device | |
KR100621003B1 (en) | Decoding method of digital image data | |
CN110493597B (en) | Efficient perceptual video coding optimization method | |
US7657110B2 (en) | Image compression using a color visual model | |
CN108737826B (en) | Video coding method and device | |
US10681350B2 (en) | Picture encoding and decoding methods and apparatuses, and picture encoding and decoding system |
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 | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right |
Effective date of registration: 20240115 Address after: 313200 Room 337, Building 3, No. 266, Zhenxing Road, Yuyue Town, Deqing County, Huzhou City, Zhejiang Province Patentee after: Huzhou Chuangguan Technology Co.,Ltd. Address before: 315211, Fenghua Road, Jiangbei District, Zhejiang, Ningbo 818 Patentee before: Ningbo University |
|
TR01 | Transfer of patent right |