CN107454425A - A kind of SCC intraframe codings unit candidate modes reduction method - Google Patents
A kind of SCC intraframe codings unit candidate modes reduction method Download PDFInfo
- Publication number
- CN107454425A CN107454425A CN201710746027.9A CN201710746027A CN107454425A CN 107454425 A CN107454425 A CN 107454425A CN 201710746027 A CN201710746027 A CN 201710746027A CN 107454425 A CN107454425 A CN 107454425A
- Authority
- CN
- China
- Prior art keywords
- formula
- scc
- depth
- gray level
- feature
- 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 13
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000000205 computational method Methods 0.000 claims description 3
- 230000004069 differentiation Effects 0.000 claims 1
- 238000005516 engineering process Methods 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000031068 symbiosis, encompassing mutualism through parasitism Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000000007 visual effect 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
- H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
- H04N19/593—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving spatial prediction techniques
-
- 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
- H04N19/103—Selection of coding mode or of prediction mode
-
- 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
- H04N19/182—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 pixel
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
Abstract
A kind of method of CU candidate modes reduction scope in SCC frames.Present invention utilizes the feature of screen content video and the Space Consistency of coding unit, by the feature for the gray level co-occurrence matrixes for calculating the coding unit that depth is 0 and 1, utilize adjacent encoder unit correlation feature, to the coding unit that depth is 0, predict whether to skip Intra patterns in advance, to the coding unit that depth is 1, predict whether to skip Intra and Palette patterns in advance.This method effectively can reduce to SCC intraframe coding unit candidate modes, so as to reduce the complexity of SCC encoders, on the premise of screen content video encoding quality is had little influence on, improve SCC encoder coding rates.
Description
Technical field：
The present invention relates to screen content to encode (Screen Content Coding, SCC) field, more particularly in SCC frames
The predictive mode decision-making technic of coding unit.
Background technology：
In recent years, with video conference, long- distance tabletop control etc. application it is more and more extensive, people for as animation, carry
The demand of the screen videos such as the image of text chart is increasing.Screen video has the characteristics of different from natural video frequency, such as
Tone is discontinuous, word or pattern edge are very sharp keen, without trappable noise, localized mass number of colors is limited and interframe
Correlation difference etc..Screen content Video coding (Screen Content Video Coding, SCC) is to be based on efficient video
The new technology proposed on coding standard (High Efficiency Video Coding, HEVC) extension framework, it is in HEVC
Some new coding techniques are with the addition of on coding unit (Coding Unit) architecture basics based on quaternary tree, to improve screen
Curtain audio content code efficiency.In order to reduce intraframe coding spatial redundancy information, SCC selected in infra-frame prediction candidate pattern
Journey, except in frame in addition to 35 kinds of predictive modes, also add many coding techniques for being directed to screen video, increase used by HEVC
Technology include intra block replicate (Intra Block Copy, IntraBC), palette (Palette) pattern,
FastIntraBC patterns, adaptive color conversion (Adaptive Colour Transform, ACT) etc., referring specifically to document 1
(JCTVC-U1014,R.Joshi,S.Liu,J.Xu,Y.Ye,"Screen content coding test model 5,"
Warsaw,Poland,June 2015.).Palette patterns are the coding techniques that SCC is newly introduced, such as document 2 (Guo L, Pu
W,Zou F,et al.Color palette for screen content coding.Image Processing(ICIP),
2014IEEE International Conference on.IEEE,2014:5556-5560.), no matter to damaging or lossless
Coding, Palette patterns can all significantly improve the efficiency of screen content Video coding, but the introducing of the pattern also increases SCC
The complexity of intraframe coding.
SCC general-utility test platform SCM8.0 intra-frame encoding mode selects flow to current maximum coding unit LCU From depth 0 to depth 3, successively different coding unit size and corresponding predictive mode are detected, and according to rate distortion generation Valency criterion determines optimal coding unit size and optimal prediction modes.For depth be 0 CU, successively detect Intra and IntraBCMerge patterns；For the CU that depth is 1, IntraBC, Intra, IntraBCMerge and Palette are detected successively Pattern；For the CU that depth is 2, IntraBC, Intra, IntraBCMerge, FastIntraBC (1DSearch) are detected successively With Palette patterns；For the CU that depth is 3, IntraBC, Intra, IntraBCMerge, FastIntraBC are detected successively (1DSearch, Hash-Search) and Palette patterns, then choose current depth by calculating rate distortion costs RD_Cost Optimization model.The complexity of SCC intraframe codings is optimized by researcher at present, and achieves good effect
Fruit, as document 4 using mean pixel cost come determine in advance the size of SCC intraframe codings (Saurty K, Catherine P C,
Soyjaudah K M.Early CU size determination in HEVC intra prediction using
Average Pixel Cost.Digital Information and Communication Technology and it's
Applications(DICTAP),2014Fourth International Conference on.IEEE,2014:247-
252.).Document 5 then proposes a kind of quick intraframe coding tree unit depth decision making algorithm based on entropy and number of coded bits
(Zhang M,Guo Y,Bai H.Fast intra partition algorithm for HEVC screen content
coding.Visual Communications and Image Processing Conference,2014 IEEE.IEEE,
2014:390-393.)。
The content of the invention：
It is an object of the invention to provide a kind of method of CU candidate modes reduction scope in SCC frames.
The main thought of the present invention is to be contracted using the strong correlation between the feature and adjacent C U of CU gray level co-occurrence matrixes
Subtract candidate modes hunting zone in the CU frames that SCC Encoder Depths are 0 and 1, reduce SCC encoder complexities.Specifically,
For the CU that depth is 0 and 1, current CU gray level co-occurrence matrixes and its 5 feature (including second moment (Angular are calculated
Second Moment, ASM), entropy (Entropy, ENT), inverse difference moment (Inverse Different Moment, IDM), from phase
Close (Correlation, COR), the moment of inertia (Moment of Inertia, MOI)), while obtain adjacent C U gray scale symbiosis square
The feature and dividing condition of battle array, wherein current CU is labeled as CurrentCU, upper, left, upper left CU adjacent thereto are marked respectively
It is as shown in Figure 1 for AboveCU, LeftCU, AboveLeftCU, its neighbouring relations.To the CU that depth is 0 and 1, present invention definition
Pattern reduction sign of flagPM.If FlagPMFor 1, to the CU that depth is 0, Intra patterns are skipped, to the CU that depth is 1,
Skip Intra and Palette patterns.If FlagPMFor 0, then according to SCCGeneral-utility test platform SCM8.0 intra-frame encoding mode Select flowPrediction.
Wherein, FlagPMCalculation formula it is as follows：
In formula (1), SPA、SPL、SPLAThe flag bit whether three adjacent C U divide is represented respectively, i.e., if division
Then corresponding flag bit is 1, is otherwise 0.SPFinalCUIt is the adjacent C U most like with CurrentCU dividing conditions division feelings
Condition, also distinguished and whether divided with 0 and 1.
The SPFinalCUComputational methods it is as follows：
First, compare AboveCU and LeftCU and CurrentCU correlation, select a CU more relevant in both
It is set to TempCU, its correlation calculations formula is as follows：
Judged according to the resulting result of formula (2), if CTempCUValue be more than 2, then TempCU be
AboveCU, it is otherwise LeftCU.Wherein,WithRepresent current CU and adjacent C U gray level co-occurrence matrixes ith features
The absolute value of difference, for reflecting texture similarity degree, its value is smaller then to prove that similarity degree is bigger,WithCalculating as public
Shown in formula (3) and formula (4),CurrentCU, LeftCU and AboveCU gray level co-occurrence matrixes are represented respectively
Ith feature.
The TempCU drawn according to above-mentioned formula calculates the correlation with CurrentCU with LeftAboveCU again, and it is counted
Formula is calculated for example shown in formula (5), and select it is more related in both be set to FinalCU, its dividing condition is in formula (1)
SPFinalCU。
Wherein,
Judged according to the resulting result of formula (5), if CFinalCUValue be more than 2, then FinalCU be then
LeftAboveCU, it is otherwise TempCU.Wherein,WithCalculating such as formula (6) and formula (7),WithGeneration respectively
The ith feature of table TempCU and LeftAboveCU gray level co-occurrence matrixes.
Using such scheme, the beneficial effects of the invention are as follows：
1. present invention utilizes the characteristics of the similitude of the feature of adjacent C U gray level co-occurrence matrixes and CU Space Consistencies,
The CU predictive mode situations that depth is 0 and 1 are analyzed, and take optimal way to reduce infra-frame prediction candidate pattern scope,
Ensure the accuracy of prediction simultaneously.
2. the present invention has considered the characteristic of SCC video sequences, it can effectively reduce prediction CU candidate pattern model
Enclose, so as in the case of hardly loss coding quality, significantly improve SCC intraframe coding efficiency, reduce SCC encoders
Complexity.
Brief description of the drawings：
Fig. 1 is current CU CU adjacent thereto position relationship.
Fig. 2 is the flow chart of the SCC intra mode decision fast algorithms based on Texture complication.
Fig. 3 gray level co-occurrence matrixes generation step-length, the graph of a relation for generating angle.
Embodiment：
Present invention utilizes the feature of screen content video and the Space Consistency of coding unit, by calculating depth as 0
With the feature of the gray level co-occurrence matrixes of 1 coding unit, using adjacent encoder unit correlation feature, to the coding that depth is 0
Unit, predict whether to skip Intra patterns in advance, to the coding unit that depth is 1, predict whether to skip in advance Intra and
Palette patterns.This method effectively can reduce to SCC intraframe coding unit candidate modes, so as to reduce SCC
The complexity of encoder, on the premise of screen content video encoding quality is had little influence on, improve SCC encoders coding speed
Degree.
The specific embodiment of the invention is described below in conjunction with accompanying drawing and provides checking.As shown in Fig. 2 details are as follows：
Step (1), based on the test platform SCM8.0 that SCC is general, start after encoding a LCU, for being compiled in present frame
Code unit, first determines whether its depth.If depth is 0 or 1, go to step (2).If depth is 2,3, go to step (4).
Step (2), calculate CU gray level co-occurrence matrixes and its feature.Gray level co-occurrence matrixes are that statistics is spatially in certain
The gray scale joint probability distribution of a pair of pixels of kind same location relation, matrix are designated as PM, its location matrix element probability distribution
It is designated as Pd(i, j), wherein d are generation step-lengths, represent the spatial relation between two pixels, and different d determines two pictures
The distance between vegetarian refreshments and generation direction θ, i, j represent two pixels, and its position relationship is as shown in figure 3, x, y generation respectively in figure
The transverse and longitudinal coordinate of table pixel, Dx、DyOffset is represented respectively.The matrix of composition is as follows：
Gray level co-occurrence matrixes are constructed it needs to be determined that three parameters, i.e. gray level L, generate direction θ, generation step-length d, the present invention
Gray level L is chosen for 64, and generation direction θ is chosen for 0 degree and 90 degree, and generation step-length d is chosen for 8.
Some features of gray level co-occurrence matrixes react the complex situations of various sizes of CU texture, what the present invention chose
Feature has second moment, entropy, inverse difference moment, auto-correlation, the moment of inertia, and wherein second moment is also known as energy, is the flat of all elements in PM
Fang He, it can react CU intensity profile situation, and entropy has reacted CU texture uniformity coefficient, and inverse difference moment has reacted the smooth of CU
Degree, the similarities of auto-correlation reaction PM in a certain direction, the moment of inertia have reacted the complexity of PM spatial distribution.Above institute
The feature calculation formula stated is as follows：
Wherein h1、h2、h3、h4、h5ASM, ENT, IDM, COR, MOI that gray level co-occurrence matrixes are calculated value are represented respectively,
Wherein, μ1、μ2、The average and variance of PM transverse and longitudinal coordinates are represented respectively, and their calculation formula is as follows：
Step (3), computation schema reduction sign of flagPMIf FlagPMDepth for 1 and CU is 0, then skips Intra
The prediction of pattern, only predict IntraBCMerge patterns；If FlagPMDepth for 1 and CU is 1, then skip Intra patterns and
The prediction of Palette patterns, carry out prediction IntraBC patterns and IntraBCMerge patterns.Otherwise, according to SCM8.0 normal streams
Journey detects intra prediction mode, goes to step (5).
FlagPMCalculation formula is as follows：
In formula (1), SPA、SPL、SPLAThe flag bit whether three adjacent C U divide is represented respectively, i.e., if division
Then corresponding flag bit is 1, is otherwise 0.SPFinalCUIt is the adjacent C U most like with CurrentCU dividing conditions division feelings
Condition, also distinguished and whether divided with 0 and 1.SPFinalCUComputational methods it is as follows：
First, compare AboveCU and LeftCU and CurrentCU correlation, select a CU more relevant in both
It is set to TempCU, its correlation calculations formula is as follows：
Wherein,
Judged according to the resulting result of formula (2), if CTempCUValue be more than 2, then TempCU be
AboveCU, it is otherwise LeftCU.Wherein,WithRepresent current CU and adjacent C U gray level co-occurrence matrixes ith features
The absolute value of difference, for reflecting texture similarity degree, its value is smaller then to prove that similarity degree is bigger,WithCalculating such as
Shown in formula (3) and formula (4),CurrentCU, LeftCU and AboveCU gray scale symbiosis square are represented respectively
The ith feature of battle array.
The TempCU drawn according to above-mentioned formula calculates the correlation with CurrentCU with LeftAboveCU again, and it is counted
Formula is calculated for example shown in formula (5), and select it is more related in both be set to FinalCU, its dividing condition is in formula (1)
SPFinalCU。
Wherein,
Judged according to the resulting result of formula (5), if CFinalCUValue be more than 2, then FinalCU be then
LeftAboveCU, it is otherwise TempCU.Wherein,WithCalculating such as formula (6) and formula (7),WithGeneration respectively
The ith feature of table TempCU and LeftAboveCU gray level co-occurrence matrixes.
Step (4), when CU depth is 2,3, intra prediction mode is detected according to SCM8.0 normal process, is gone to step (5).
Step (5), recurrence obtain optimal depth and optimization model, current LCU end-of-encodes.
Table 1 is experimental result of the SCC algorithms of inventive algorithm and standard under SCM8.0 platforms.Test configurations are selected respectively
Take two kinds of RA and LD.The QP of selection is 22,27,32 and 27.The resolution ratio of test video is 1920 × 1080 and 1280 × 720.
Test video chooses tri- kinds of YUV444, YUV420, RGB444.On average, YUV444 format video, time save about
16%, BD-Rate rise about 1.34%；The video of YUV420 forms, time save about 20%, BD-Rate and risen about
1.1%；The video of RGB444 forms, time save about 14%, BD-Rate and rise about 1.06%.
The experimental result (%) of the inventive algorithm of table 1 and the SCC algorithms of standard under SCM8.0 platforms
Claims (3)
1. a kind of method of CU candidate modes reduction scope in SCC frames, it is characterised in that main thought of the invention is profit
It is in 0 and 1 CU frames with the strong correlation reduction SCC Encoder Depths between the feature and adjacent C U of CU gray level co-occurrence matrixes
Candidate modes hunting zone, reduce SCC encoder complexities.Specifically, for the CU that depth is 0 and 1, current CU is calculated
Gray level co-occurrence matrixes and its 5 feature (including second moment (Angular Second Moment, ASM), entropy (Entropy,
ENT), inverse difference moment (Inverse Different Moment, IDM), auto-correlation (Correlation, COR), the moment of inertia
(Moment of Inertia, MOI)), while the feature and dividing condition of adjacent C U gray level co-occurrence matrixes are obtained, wherein
Current CU is labeled as CurrentCU, upper, left, upper left CU adjacent thereto be respectively labeled as AboveCU, LeftCU,
AboveLeftCU.To the CU that depth is 0 and 1, invention defines pattern to reduce sign of flagPM.If FlagPMFor 1, to depth
The CU for 0 is spent, skips Intra patterns, to the CU that depth is 1, skips Intra and Palette patterns.If FlagPMFor 0, then
According to SCCGeneral-utility test platform SCM8.0 intra-frame encoding mode selection flowPrediction.
2. the method as described in claim 1, it is characterised in that the FlagPMCalculation formula it is as follows：
In formula (1), SPA、SPL、SPLARepresent the flag bit whether three adjacent C U divide respectively, i.e., it is corresponding if division
Flag bit be 1, be otherwise 0.SPFinalCUIt is the adjacent C U most like with CurrentCU dividing conditions dividing condition, also uses
Whether 0 and 1 differentiation divides.
3. method as claimed in claim 2, it is characterised in that the SPFinalCUComputational methods it is as follows：
First, compare AboveCU and LeftCU and CurrentCU correlation, select a CU more relevant in both and be set to
TempCU, its correlation calculations formula are as follows：
Wherein,
Judged according to the resulting result of formula (2), if CTempCUValue be more than 2, then TempCU is AboveCU, no
It is then LeftCU.Wherein,WithCurrent CU and adjacent C U gray level co-occurrence matrixes ith features poor absolute value are represent,
For reflecting texture similarity degree, its value is smaller then to prove that similarity degree is bigger,WithCalculating such as formula (3) and formula
(4) shown in,The ith feature of CurrentCU, LeftCU and AboveCU gray level co-occurrence matrixes is represented respectively.
The TempCU drawn according to above-mentioned formula calculates the correlation with CurrentCU with LeftAboveCU again, and it calculates public
Shown in formula such as formula (5), and select it is more related in both be set to FinalCU, its dividing condition is in formula (1)
SPFinalCU。
Wherein,
Judged according to the resulting result of formula (5), if CFinalCUValue be more than 2, then FinalCU be then
LeftAboveCU, it is otherwise TempCU.Wherein,WithCalculating such as formula (6) and formula (7),WithGeneration respectively
The ith feature of table TempCU and LeftAboveCU gray level co-occurrence matrixes.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710746027.9A CN107454425B (en) | 2017-08-26 | 2017-08-26 | A kind of SCC intraframe coding unit candidate modes reduction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710746027.9A CN107454425B (en) | 2017-08-26 | 2017-08-26 | A kind of SCC intraframe coding unit candidate modes reduction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107454425A true CN107454425A (en) | 2017-12-08 |
| CN107454425B CN107454425B (en) | 2019-10-18 |
Family
ID=60494175
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710746027.9A Expired - Fee Related CN107454425B (en) | 2017-08-26 | 2017-08-26 | A kind of SCC intraframe coding unit candidate modes reduction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107454425B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109688414A (en) * | 2018-12-19 | 2019-04-26 | 同济大学 | A kind of reduction of VVC intraframe coding unit candidate modes and block, which divide, shifts to an earlier date terminating method |
| CN111307560A (en) * | 2020-03-05 | 2020-06-19 | 同济大学 | Automatic urine cell staining device and control system |
| CN111836051A (en) * | 2019-04-15 | 2020-10-27 | 深信服科技股份有限公司 | Desktop image coding and decoding methods and related devices |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015070801A1 (en) * | 2013-11-14 | 2015-05-21 | Mediatek Singapore Pte. Ltd. | Method of video coding using prediction based on intra picture block copy |
| CN105430407A (en) * | 2015-12-03 | 2016-03-23 | 同济大学 | Fast inter-frame mode decision methods applied to transcoding from H.264 to HEVC |
| CN106162195A (en) * | 2016-07-05 | 2016-11-23 | 宁波大学 | A kind of 3D HEVC deep video information concealing method based on single depth frame internal schema |
| CN106210721A (en) * | 2016-07-05 | 2016-12-07 | 中南大学 | A kind of HEVC quick code check code-transferring method |
| CN106534860A (en) * | 2016-11-21 | 2017-03-22 | 天津大学 | Screen content coding method based on content analysis |
| CN106534846A (en) * | 2016-11-18 | 2017-03-22 | 天津大学 | Method for dividing and quickly encoding screen contents and natural contents |
| CN106791876A (en) * | 2016-12-16 | 2017-05-31 | 浙江大学 | A kind of depth map fast intra-frame predicting method based on 3D HEVC |
| CN106797469A (en) * | 2014-10-06 | 2017-05-31 | Vid拓展公司 | The improved palette coding for screen content coding |
-
2017
- 2017-08-26 CN CN201710746027.9A patent/CN107454425B/en not_active Expired - Fee Related
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015070801A1 (en) * | 2013-11-14 | 2015-05-21 | Mediatek Singapore Pte. Ltd. | Method of video coding using prediction based on intra picture block copy |
| CN106797469A (en) * | 2014-10-06 | 2017-05-31 | Vid拓展公司 | The improved palette coding for screen content coding |
| CN105430407A (en) * | 2015-12-03 | 2016-03-23 | 同济大学 | Fast inter-frame mode decision methods applied to transcoding from H.264 to HEVC |
| CN106162195A (en) * | 2016-07-05 | 2016-11-23 | 宁波大学 | A kind of 3D HEVC deep video information concealing method based on single depth frame internal schema |
| CN106210721A (en) * | 2016-07-05 | 2016-12-07 | 中南大学 | A kind of HEVC quick code check code-transferring method |
| CN106534846A (en) * | 2016-11-18 | 2017-03-22 | 天津大学 | Method for dividing and quickly encoding screen contents and natural contents |
| CN106534860A (en) * | 2016-11-21 | 2017-03-22 | 天津大学 | Screen content coding method based on content analysis |
| CN106791876A (en) * | 2016-12-16 | 2017-05-31 | 浙江大学 | A kind of depth map fast intra-frame predicting method based on 3D HEVC |
Non-Patent Citations (1)
| Title |
|---|
| 王菲: "基于调色板模式的屏幕视频帧内编码快速算法", 《微型机与应用》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109688414A (en) * | 2018-12-19 | 2019-04-26 | 同济大学 | A kind of reduction of VVC intraframe coding unit candidate modes and block, which divide, shifts to an earlier date terminating method |
| CN111836051A (en) * | 2019-04-15 | 2020-10-27 | 深信服科技股份有限公司 | Desktop image coding and decoding methods and related devices |
| CN111836051B (en) * | 2019-04-15 | 2023-07-14 | 深信服科技股份有限公司 | Desktop image encoding and decoding method and related device |
| CN111307560A (en) * | 2020-03-05 | 2020-06-19 | 同济大学 | Automatic urine cell staining device and control system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107454425B (en) | 2019-10-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lei et al. | Fast intra prediction based on content property analysis for low complexity HEVC-based screen content coding | |
| CN101507277B (en) | Image encoding/decoding method and apparatus | |
| CN104780364B (en) | Determine the intra prediction mode of image coding unit and image decoding unit | |
| JP5503747B2 (en) | Image encoding device, image decoding device, image encoding method, and image decoding method | |
| CN105847792B (en) | Dynamic image encoding device and image encoding method | |
| CN103517069A (en) | HEVC intra-frame prediction quick mode selection method based on texture analysis | |
| TWI706671B (en) | Dynamic picture encoding apparatus, dynamic picture decoding apparatus, dynamic picture encoding method, dynamic picture decoding method, and storage media dynamic picture encoding data | |
| JP2008245088A (en) | Intra prediction system for moving image encoding apparatus and moving image decoding apparatus | |
| CN100591136C (en) | Video frequency intraframe coding method based on null field decomposition | |
| CN105103547A (en) | Color image encoding apparatus, color image decoding apparatus, color image encoding method, and color image decoding method | |
| Wang et al. | An Information Hiding Algorithm for HEVC Based on Angle Differences of Intra Prediction Mode. | |
| CN107454425B (en) | A kind of SCC intraframe coding unit candidate modes reduction method | |
| CN102934445B (en) | Based on the method and apparatus of segmentation to image coding and decoding | |
| WO2016060672A1 (en) | Video coding using a saliency map | |
| CN115190312B (en) | Cross-component chromaticity prediction method and device based on neural network | |
| KR101073938B1 (en) | Method for encoding image using estimation of color space | |
| CN106878754A (en) | A kind of 3D video depths image method for choosing frame inner forecast mode | |
| CN104244008B (en) | Depth video coding method | |
| CN113992911A (en) | Intra-frame prediction mode determination method and device for panoramic video H264 coding | |
| CN109889831A (en) | 360 degree of video intra mode decisions based on CU size | |
| JP2024000443A (en) | Video image coding device and program | |
| JP2008017304A (en) | Image coding device, image decoding device, image coding method, and image coding program | |
| Fan et al. | A fast depth intra mode selection algorithm | |
| JP2023049881A (en) | Video encoder and program | |
| CN116156187A (en) | Image processing method, device, electronic equipment and storage medium |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20191018 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |