CN105208387B - A kind of HEVC Adaptive Mode Selection Method for Intra-Prediction - Google Patents
A kind of HEVC Adaptive Mode Selection Method for Intra-Prediction Download PDFInfo
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Abstract
The present invention relates to a kind of HEVC Adaptive Mode Selection Method for Intra-Prediction, comprise the following steps：（1）A PU to be estimated is inputted, establishes actually available intra prediction mode set；（2）Calculate all pixels in PU to be estimated be different from director space adjacent pixel poor absolute value and；（3）According to the absolute difference of different directions spatial neighborhood pixels and the grain direction characteristic for judging PU to be estimated；（4）Thick level pattern search scope is determined according to grain direction characteristic；（5）Rate-distortion optimization candidate pattern set is established according to thick level pattern search scope and actually available intra prediction mode set；（6）Choose optimal intra prediction mode.The present invention first reduces the thick level hunting zone of predictive mode according to PU to be estimated grain direction feature, the candidate pattern number for carrying out rate-distortion optimization is reduced again, and the computation complexity of HEVC Intra prediction mode selections can be significantly reduced while well encoded distortion performance is kept.
Description
Technical field
The present invention relates to digital video coding field, and in particular to a kind of HEVC Adaptive Mode Selection Method for Intra-Prediction.
Background technology
With the fast development of multimedia technology, the video datas of various resolution ratio (including SD, high definition and ultra high-definition regard
Frequently occur in succession), the transmission of video data and storage faces enormous challenge.To meet the development of video data compression and transmission
Demand, Video coding joint specialist group (the Joint Collaborative Team on organized by ISO/IEC and ITU-T
Video Coding, JCT-VC) formulate high efficiency video encoding standard (High Efficiency Video of new generation
Coding,HEVC/H.265).Under identical video quality, HEVC with prior-generation video encoding standard H.264 compared with reduce
The code stream of half or so is (see G.J.Sullivan, J.-R.Ohm, W.-J.Han, and T.Wiegand, Overview of
The high efficiency video coding (HEVC) standard, i.e., " general introduction of high efficiency video encoding standard ",
IEEE Transactions on Circuits and Systems for Video Technology,vol.22,no.12,
Pp.1649-1668, Dec.2012), i.e., code efficiency is doubled, but its computation complexity increase several times.Although HEVC
Mixed coding technology is equally used with traditional video encoding standard, introduces newly encoded technology, such as code tree list in many aspects
The inter prediction of first (Coding Tree Unit, CTU) quad-tree partition, multi-angle intra prediction mode and a variety of dividing modes
Pattern etc..In order to which more neatly coded image, HEVC propose three kinds of partition modes, respectively coding unit (Coding
Unit, CU), predicting unit (Prediction Unit, PU) and converter unit (Transform Unit).HEVC PU predictions
Process includes inter prediction and infra-frame prediction, and for wherein I frames or the PU of every IDR frame all only with infra-frame prediction, other type frames can be with
Use infra-frame prediction and inter prediction simultaneously.In order to improve the compression efficiency of infra-frame prediction, HEVC is using existing sky around PU
Between adjacent reconstruction pixel carry out infra-frame prediction, can at most use 35 kinds of intra prediction modes (see J.Lainema,
F.Bossen, W.-J Han, J.Min, and K.Ugur, Intra coding of the HEVC standard, i.e. " HEVC
The intraframe coding of standard ", IEEE Transactions on Circuits and Systems for Video
Technology,vol.22,no.12,pp.1792-1801,Dec.2012).In HEVC all intra prediction modes, compile
Number 0 Planar patterns and the DC patterns of numbering 1 are applied to flat site, the 33 kinds of angle predictive modes of correspondence of numbering 2~34, its
In, horizontally right direction is predicted the angle predictive mode of numbering 10, and the angle predictive mode of numbering 26 is along straight down
Direction is predicted, and the angle predictive mode of numbering 18 is diagonally predicted toward lower right, the angle prediction mould of numbering 2
Formula is diagonally predicted toward upper right, and the angle predictive mode of numbering 34 is diagonally predicted toward lower left.
In HEVC test model HM, intra-prediction process first to carry out thick level mode decision (Rough Mode Decision,
RMD), the absolute error after the residual signals Hadamard transform by calculating PU and (Sum of Absolute Transformed
Difference, SATD) carry out preliminary screening predictive mode, for the PU that size is 4 × 4 and 8 × 8, choose 8 kinds of predictive modes and make
For candidate pattern, for the PU that size is 16 × 16,32 × 32 and 64 × 64, choose 3 kinds of predictive modes as candidate pattern (see
L.Zhao,L.Zhang,X.Zhao,S.Ma,D.Zhao,W.Gao,Further encoder improvement for intra
Mode decision (JCTVC-D283), i.e. " the further optimization of intra mode decision in cataloged procedure ", Proceedings
of the JCT-VC 4th meeting,pp.1-4,Jan.2011).Then rate-distortion optimization (Rate Distortion are used
Optimization, RDO) technology (see Wiegand T, Schwarz H, Joch A, Kossentini F, Sullivan G J,
Rate-constrained coder control and comparison of video coding standards, i.e., " depending on
The restricted encoder of code check of frequency coding standard is controlled and compared ", IEEE Transactions on Circuits and
Systems for Video Technology,2003,13(7):688-703), the selection rate distortion generation from some candidate patterns
The minimum pattern of valency is as optimum prediction mode in PU frame.HEVC intra prediction modes more can than H.264 more rich and varied
It is adapted to coding high-resolution video, but which increases the computation complexity of HEVC intraframe codings.
Has some HEVC Adaptive Mode Selection Method for Intra-Prediction at present.Application No. 201210138816.1 it is special
Candidate modes number is reduced to by profit during RMD for the PU that size is 4 × 4 and 8 × 8,16 × 16 and 32 × 32
2~5.Qi Mei is refined et al. to propose a kind of HEVC intra mode decisions based on image texture direction and spatial coherence quickly side
(see Qi Meibin, Zhu Guanghui, Yang Yanfang, Jiang Jianguo utilize texture and the HEVC Intra prediction mode selections of spatial coherence to method
[J] Journal of Image and Graphics, 2014,19 (8), 1119-1125).The PU texture sides that this method is obtained using Sobel operators
Always establish and be selected predictive mode list, and optimum prediction mode in the adjacent PU frames based on spatial coherence is added into the row
Table.Application No. 201410842187.X patent provides a kind of HEVC Intra prediction mode selections accelerated method.In the party
In method, if PU has texture homogeneity feature, RMD the 1st predictive mode chosen directly is chosen for optimal infra-frame prediction
Pattern；Secondly RMD preceding 2 predictive modes chosen are divided into the different situation of 3 classes to accelerate model selection.Waited with above-mentioned reduction
The method for selecting predictive mode is different, and the patent of Application No. 201410024635.5 proposes a kind of HEVC fast frames based on SATD
Interior prediction method, the computation complexity of HEVC infra-frame prediction is reduced by terminating CU division.This method is calculated by SATD
Go out one group of adaptable threshold value, if current CU SATD is less than given threshold value, terminate CU division.And Application No.
201310445775.5 patent on the one hand according to Texture complication determine CU divide；On the other hand, according to PU texture features
Some predictive modes for most unlikely turning into optimal mode are deleted from candidate modes list.
The content of the invention
For the computation complexity of effective reduction HEVC infra-frame predictions under conditions of keeping encoding distortion performance, this hair
It is bright to provide a kind of HEVC Adaptive Mode Selection Method for Intra-Prediction.
In order to solve the above-mentioned technical problem the technical scheme used for：
A kind of HEVC Adaptive Mode Selection Method for Intra-Prediction, described method comprise the following steps：
(1) PU to be estimated is inputted, establishes actually available intra prediction mode set：
Needed according to the adjacent reconstruction pixel in existing space around PU to be estimated and each HEVC intra prediction modes
The adjacent reconstruction pixel in space, all actually available intra prediction modes are chosen for PU to be estimated, form set omega, i.e., to each
HEVC intra prediction modes, if the existing pattern carries out the adjacent reconstruction picture in space of infra-frame prediction needs around PU to be estimated
Element, then the pattern is added to Ω.
(2) calculate all pixels in PU to be estimated be different from direction spatial neighborhood pixels absolute difference and：
For 33 kinds of angle predictive modes of HEVC intra prediction modes, PU to be estimated grain direction characteristic and the PU are most
The angle predictive mode chosen eventually has correlation.Therefore, can be adjacent with its space by calculating the pixel in PU to be estimated
The poor absolute value of pixel and PU to be estimated grain direction characteristic is determined, quickly to select intra prediction mode.
First, when the angle predictive mode that numbering is 18 in Ω be present, i.e., PU to be estimated can be used and diagonally turned right
The angle predictive mode that lower direction is predicted, then calculate all pixels and the difference of its upper left side adjacent pixel in PU to be estimated
Absolute value and SADLU, as shown in formula (1)：
In formula (1), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than or equal to N-1, coordinate is the upper left side that the pixel of (x-1, y-1) is located at that coordinate is (x, y).Coordinate is
The pixel of (- 1, -1) is the top left pixel for the pixel that coordinate is (0,0), and coordinate is PU upper lefts top to be estimated for the pixel of (0,0)
The pixel of Angle Position, coordinate are the pixel that the pixel of (0, N-1) is PU lower-lefts to be estimated corner position, and coordinate is (N-1,0)
Pixel is the pixel of PU upper rights corner position to be estimated, and coordinate is PU bottom rights to be estimated corner position for the pixel of (N-1, N-1)
Pixel.Coordinate is the coboundary pixel that the pixel of (0, y) is PU to be estimated, and coordinate is PU to be estimated for the pixel of (x, 0)
Left margin pixel, coordinate are the right margin pixel that the pixel of (N-1, y) is PU to be estimated, and coordinate is to treat for the pixel of (x, N-1)
Estimate PU lower boundary pixel.
Similarly, when the angle predictive mode that numbering is 26 in Ω be present, i.e., PU to be estimated can use side straight down
To the angle predictive mode being predicted, then all pixels and the absolute difference of its top adjacent pixel in PU to be estimated are calculated
And SADU, as shown in formula (2)：
In formula (2), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the surface that the pixel of (x, y-1) is located at that coordinate is (x, y).
When the angle predictive mode that numbering is 34 in Ω be present, i.e., PU to be estimated can be entered using diagonally lower left
The angle predictive mode of row prediction, then calculate in PU to be estimated the absolute difference of all pixels and its upper right side adjacent pixel and
SADRU, as shown in formula (3)：
In formula (3), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the upper right side that the pixel of (x+1, y-1) is located at that coordinate is (x, y).
When the angle predictive mode that numbering is 10 in Ω be present, i.e., it is pre- that PU to be estimated can use horizontal right direction to carry out
The angle predictive mode of survey, then calculate all pixels and the absolute difference and SAD of its left adjacent pixel in PU to be estimatedL,
As shown in formula (4)：
In formula (4), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the left that the pixel of (x-1, y) is located at that coordinate is (x, y).
When the angle predictive mode that numbering is 2 in Ω be present, i.e., PU to be estimated can be entered using diagonally upper right
The angle predictive mode of row prediction, then calculate in PU to be estimated the absolute difference of all pixels and its lower left adjacent pixel and
SADLB, as shown in formula (5)：
In formula (5), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the lower left that the pixel of (x-1, y+1) is located at that coordinate is (x, y).
(3) according to the absolute difference of different directions spatial neighborhood pixels and the line for judging PU to be estimated
Manage directional characteristic：
First, step selection is carried out according to the absolute difference being calculated from step (2) and SAD number：If step
(2) SAD number is calculated less than 3, then performs step (5)；Otherwise the SAD that first step (2) is calculated carry out from it is small to
Longer spread, if first three minimum SAD is followed successively by SADMIN-0、SADMIN-1And SADMIN-2；It is right further according to these three minimum SAD
PU to be estimated textural characteristics are classified, as shown in formula (6):
In formula (6), Class represents PU to be estimated texture classification, is worth and represents that PU to be estimated texture is relatively flat for 0,
It is worth and represents that significantly horizontal, vertical or diagonal is presented in PU to be estimated texture for 1, is worth and represents PU's to be estimated for 2
Other angle directions are presented in texture, are worth and represent that PU to be estimated texture is complicated for 3, parameter alpha, β and γ are used to adjust SADMIN-i(i
=0,1,2) relation between, wherein α are set to 0.9~1.0, β and γ is set to 0.6~1.0.
Then PU texture classification Class and the SAD relations being calculated by formula (6), obtain PU grain directions to be estimated
Characteristic, as shown in table 1.In table 1,0 degree of direction refers to horizontally right direction, and pi/2 direction refers to along vertically downward direction, π/
4 directions refer to along 45 degree of bottom right direction, and the direction of-π/4 refers to along 45 degree of directions of upper right, and the direction of 3 π/4 refers to along 45 degree of lower-left side
To.When texture classification Class is equal to 0, it is flatter that PU to be estimated grain direction characteristic is designated as texture.As texture classification Class
Equal to 1, PU to be estimated grain direction characteristic is according to SADMIN-0Whether SAD is equal toLU、SADU、SADRU、SADLAnd SADLBRespectively
It is in 0 degree of direction and texture in the direction of 3 π/4, texture in pi/2 direction, texture that PU to be estimated is designated as into texture in the direction of π/4, texture
In the direction of-π/4.When texture classification Class is equal to 2, PU to be estimated grain direction characteristic is according to SADMIN-0And SADMIN-1Value
Whether it is SADLU、SADU、SADRU、SADLAnd SADLBIn two sad values in adjacent direction differentiate PU to be estimated grain direction
Characteristic：If (a) SADLUEqual to SADMIN-0And SADUEqual to SADMIN-1, or SADLUEqual to SADMIN-1And SADUIt is equal to
SADMIN-0, then it is in [π/4, pi/2] direction grain direction characteristic to be designated as into texture；If (b) SADUEqual to SADMIN-0And SADRUDeng
In SADMIN-1, or SADUEqual to SADMIN-1And SADRUEqual to SADMIN-0, then by grain direction characteristic be designated as texture in [pi/2,3
π/4] direction；If (c) SADLUEqual to SADMIN-0And SADLEqual to SADMIN-1, or SADLUEqual to SADMIN-1And SADLIt is equal to
SADMIN-0, then it is in [0, π/4] direction grain direction characteristic to be designated as into texture；If (d) SADLEqual to SADMIN-0And SADLBIt is equal to
SADMIN-1, or SADLEqual to SADMIN-1And SADLBEqual to SADMIN-0, then it is in [- π/4,0] grain direction characteristic to be designated as into texture
Direction；(f) other situations, then grain direction characteristic is designated as complex texture direction.When texture classification Class be equal to 3, it is to be estimated
PU grain direction characteristic is designated as complex texture direction.
The PU grain directions characteristic to be estimated of table 1
(4) thick level pattern search scope is determined according to grain direction characteristic：
According to PU to be estimated grain direction characteristic, the predictive mode species of candidate, the predictive mode group after adjustment are reduced
Into thick level pattern search scope S, the predictive mode in wherein S is set according to PU to be estimated grain direction characteristic, as follows
Shown in table 2：
Predictive mode in the S of table 2
(5) rate-distortion optimization candidate pattern set is established according to thick level hunting zone and Ω：
From the predictive mode hunting zone that step (4) obtains, predictive mode number is still more in some cases, therefore
Need to carry out further to screen predictive mode before step (6) uses rate-distortion optimization choice of technology optimum prediction mode.
SATD cost pattern search scopes Ψ is determined first：If going to current procedures from step (4), Ψ is step
(4) the thick level pattern search scope S obtained obtains Ω common factor with step (1), if going to current procedures from step (3),
Ω is directly then assigned to Ψ.
Then the HEVC intra predictions of each predictive mode in Ψ are calculated, then calculate the SATD cost J of prediction residual,
As shown in formula (7)：
J=SATD+ λ × R (7)
Wherein J represent cost, SATD represent residual signals Hadamard transform after absolute error and, λ represent Lagrange
Operator, required bit number is encoded after the selection of R intermediate schemes.
Each predictive mode is ranked up then according to the orders of SATD costs J from small to large, after sequence
Predictive mode establishes rate-distortion optimization candidate pattern set Φ：When the predictive mode for being arranged in the 1st is DC patterns or Planar
Pattern, then the predictive mode of 1 before arrangement is only added into Φ；When the predictive mode for being arranged in the 1st is angle mode and the 2nd
Predictive mode be DC patterns or Planar patterns, then the predictive mode of 2 before arrangement is only added into Φ；When being arranged in front 2
Predictive mode be all adjacent angle mode, then only by before arrangement 2 predictive mode add Φ；When being arranged in front 2
Predictive mode is non-conterminous angle mode, then the predictive mode of 2 before arrangement first is added into Φ, then by 2 kinds of predictive modes
Adjacent angle mode adds Φ；In other cases, for size be 16 × 16,32 × 32 and 64 × 64 PU to be estimated,
The predictive mode of 3 before arrangement is then added into Φ, for the PU to be estimated that size is 4 × 4 and 8 × 8, then by 8 before arrangement
Predictive mode adds Φ.
(6) optimal intra prediction mode is chosen：
Rate distortion costs minimum is chosen in the candidate pattern set Φ obtained using rate-distortion optimization technology from step (5)
Optimal intra prediction mode of the candidate pattern as PU to be estimated, complete PU to be estimated Intra prediction mode selection.
The present invention technical concept be：All pixels point in PU is calculated first is different from director space adjacent pixel
SAD, PU texture features are drawn, to determine grain direction feature；Then according to grain direction feature, establish thick level pattern and search
Rope scope, reduce the candidate pattern number for carrying out thick level pattern search；Rate-distortion optimization candidate pattern set is finally established, enters one
Step reduces the final candidate pattern number for carrying out rate-distortion optimization.
Compared with prior art, the invention has the advantages that：
The present invention proposes a kind of HEVC Adaptive Mode Selection Method for Intra-Prediction.This method compared with prior art, has
Following features and advantage：First by comparing the absolute difference of each original pixels in different directions and realization pair inside PU
PU grain direction feature is classified；The hunting zone of predictive mode is reduced further according to grain direction feature；Last basis
The sequence of predictive mode SATD costs carries out the candidate pattern number of rate-distortion optimization to reduce.Keeping good encoding rate distortion
Under conditions of performance, the Intra prediction mode selection that the present invention can significantly decrease in HEVC frames and in inter-frame encoding frame calculates again
Miscellaneous degree.
Brief description of the drawings
Fig. 1 is the basic flow sheet of the inventive method.
Fig. 2 is that HEVC encodes angle predictive mode in 33 kinds of frames.
Embodiment
The present invention is described in detail with reference to embodiment and accompanying drawing, but the present invention is not limited to this.
As shown in figure 1, a kind of HEVC Adaptive Mode Selection Method for Intra-Prediction, comprises the following steps：
(1) PU to be estimated is inputted, establishes actually available intra prediction mode set；
(2) calculate all pixels in PU to be estimated be different from direction spatial neighborhood pixels absolute difference and；
(3) according to the absolute difference of different directions spatial neighborhood pixels and the grain direction characteristic for judging PU to be estimated；
(4) thick level pattern search scope is determined according to grain direction characteristic；
(5) rate-distortion optimization candidate is established according to thick level pattern search scope and actually available intra prediction mode set
Set of modes；
(6) optimal intra prediction mode is chosen.
Step (1) specifically includes：
Needed according to the adjacent reconstruction pixel in existing space around PU to be estimated and each HEVC intra prediction modes
The adjacent reconstruction pixel in space, all actually available intra prediction modes are chosen for PU to be estimated, form set omega, i.e., to each
HEVC intra prediction modes, if the existing pattern carries out the adjacent reconstruction picture in space of infra-frame prediction needs around PU to be estimated
Element, then the pattern is added to Ω.
Step (2) specifically includes：
First, when the angle predictive mode that numbering is 18 in Ω be present, i.e., PU to be estimated can be used and diagonally turned right
The angle predictive mode that lower direction is predicted, then calculate all pixels and the difference of its upper left side adjacent pixel in PU to be estimated
Absolute value and SADLU, as shown in formula (1)：
In formula (1), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than or equal to N-1, coordinate is the upper left side that the pixel of (x-1, y-1) is located at that coordinate is (x, y).Coordinate is
The pixel of (- 1, -1) is the top left pixel for the pixel that coordinate is (0,0), and coordinate is PU upper lefts top to be estimated for the pixel of (0,0)
The pixel of Angle Position, coordinate are the pixel that the pixel of (0, N-1) is PU lower-lefts to be estimated corner position, and coordinate is (N-1,0)
Pixel is the pixel of PU upper rights corner position to be estimated, and coordinate is PU bottom rights to be estimated corner position for the pixel of (N-1, N-1)
Pixel.In HEVC standard, its prediction direction of the angle predictive mode of difference numbering is as shown in Figure 2.
Similarly, when the angle predictive mode that numbering is 26 in Ω be present, i.e., PU to be estimated can use side straight down
To the angle predictive mode being predicted, then all pixels and the absolute difference of its top adjacent pixel in PU to be estimated are calculated
And SADU, as shown in formula (2)：
In formula (2), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the surface that the pixel of (x, y-1) is located at that coordinate is (x, y).
When the angle predictive mode that numbering is 34 in Ω be present, i.e., PU to be estimated can be entered using diagonally lower left
The angle predictive mode of row prediction, then calculate in PU to be estimated the absolute difference of all pixels and its upper right side adjacent pixel and
SADRU, as shown in formula (3)：
In formula (3), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the upper right side that the pixel of (x+1, y-1) is located at that coordinate is (x, y).
When the angle predictive mode that numbering is 10 in Ω be present, i.e., it is pre- that PU to be estimated can use horizontal right direction to carry out
The angle predictive mode of survey, then calculate all pixels and the absolute difference and SAD of its left adjacent pixel in PU to be estimatedL,
As shown in formula (4)：
In formula (4), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the left that the pixel of (x-1, y) is located at that coordinate is (x, y).
When the angle predictive mode that numbering is 2 in Ω be present, i.e., PU to be estimated can be entered using diagonally upper right
The angle predictive mode of row prediction, then calculate in PU to be estimated the absolute difference of all pixels and its lower left adjacent pixel and
SADLB, as shown in formula (5)：
In formula (5), PU to be estimated size is N × N (N=4,8,16,32,64), and p (x, y) is coordinate in PU to be estimated
For the pixel value of the pixel of (x, y), wherein x is horizontal coordinate, and y is vertical coordinate, in PU to be estimated their value be more than
Integer equal to 0 and less than N, coordinate is the lower left that the pixel of (x-1, y+1) is located at that coordinate is (x, y).
Step (3) specifically includes：
First, step selection is carried out according to SAD number of the absolute difference being calculated from step (2)：If step (2)
SAD number is calculated less than 3, then performs step (5)；Otherwise the SAD first step (2) being calculated is arranged from small to large
Row, if first three minimum SAD is followed successively by SADMIN-0、SADMIN-1And SADMIN-2；Further according to these three minimum SAD, treat and estimate
Meter PU textural characteristics are classified, as shown in formula (6):
In formula (6), Class represents PU to be estimated texture classification, is worth and represents that PU to be estimated texture is relatively flat for 0,
It is worth and represents that significantly horizontal, vertical or diagonal is presented in PU to be estimated texture for 1, is worth and represents PU's to be estimated for 2
Other angle directions are presented in texture, are worth and represent that PU to be estimated texture is complicated for 3, parameter alpha, β and γ are used to adjust SADMIN-i(i
=0,1,2) relation between, wherein α are set to 0.9~1.0, β and γ and are set to 0.6~1.0, and α is set to 0.95, β and γ herein
It is set to 0.9.
Then PU texture classification Class and the SAD relations being calculated by formula (6), obtain PU grain directions to be estimated
Characteristic, as shown in table 1.In table 1,0 degree of direction refers to horizontally right direction, and pi/2 direction refers to along vertically downward direction, π/
4 directions refer to along 45 degree of bottom right direction, and the direction of-π/4 refers to along 45 degree of directions of upper right, and the direction of 3 π/4 refers to along 45 degree of lower-left side
To.When texture classification Class is equal to 2, PU to be estimated grain direction characteristic is according to SADMIN-0And SADMIN-1Value whether be
SADLU、SADU、SADRU、SADLAnd SADLBIn two sad values in adjacent direction differentiate PU to be estimated grain direction characteristic：
If (a) SADLUEqual to SADMIN-0And SADUEqual to SADMIN-1, or SADLUEqual to SADMIN-1And SADUEqual to SADMIN-0, then
It is in [π/4, pi/2] direction that grain direction characteristic is designated as into texture；If (b) SADUEqual to SADMIN-0And SADRUEqual to SADMIN-1,
Or SADUEqual to SADMIN-1And SADRUEqual to SADMIN-0, then it is in [pi/2,3 π/4] direction grain direction characteristic to be designated as into texture；
If (c) SADLUEqual to SADMIN-0And SADLEqual to SADMIN-1, or SADLUEqual to SADMIN-1And SADLEqual to SADMIN-0, then
It is in [0, π/4] direction that grain direction characteristic is designated as into texture；If (d) SADLEqual to SADMIN-0And SADLBEqual to SADMIN-1, or
Person SADLEqual to SADMIN-1And SADLBEqual to SADMIN-0, then it is in [- π/4,0] direction grain direction characteristic to be designated as into texture；(f)
Other situations, then grain direction characteristic is designated as complex texture direction.When texture classification Class be equal to 3, PU to be estimated texture
Directional characteristic is designated as complex texture direction.
The PU grain directions characteristic to be estimated of table 1
Step (4) specifically includes：
According to PU to be estimated grain direction characteristic, the predictive mode species of candidate, the predictive mode group after adjustment are reduced
Into the thick level pattern search scope S of predictive mode, the predictive mode in wherein S be according to PU to be estimated grain direction characteristic come
Set, it is as shown in table 2 below：
Predictive mode in the S of table 2
Step (5) specifically includes：
SATD cost pattern search scopes Ψ is determined first：If going to current procedures from step (4), Ψ is step
(4) the thick level pattern search scope S obtained obtains Ω common factor with step (1), if going to current procedures from step (3),
Ω is directly then assigned to Ψ.
Then the HEVC intra predictions of each predictive mode in Ψ are calculated, then calculate the SATD costs of prediction residual,
As shown in formula (7)：
J=SATD+ λ × R (7)
Wherein J represent cost, SATD represent residual signals Hadamard transform after absolute error and, λ represent Lagrange
Operator, required bit number is encoded after the selection of R intermediate schemes.
Each predictive mode is ranked up then according to the orders of SATD costs J from small to large, after sequence
Predictive mode establishes rate-distortion optimization candidate pattern set Φ：When the predictive mode for being arranged in the 1st is DC patterns or Planar
Pattern, then the predictive mode of 1 before arrangement is only added into Φ；When the predictive mode for being arranged in the 1st is angle mode and the 2nd
Predictive mode be DC patterns or Planar patterns, then the predictive mode of 2 before arrangement is only added into Φ；When being arranged in front 2
Predictive mode be all adjacent angle mode, then only by before arrangement 2 predictive mode add Φ；When being arranged in front 2
Predictive mode is non-conterminous angle mode, then the predictive mode of 2 before arrangement first is added into Φ, then by 2 kinds of predictive modes
Adjacent angle mode adds Φ；In other cases, for size be 16 × 16,32 × 32 and 64 × 64 PU to be estimated,
The predictive mode of 3 before arrangement is then added into Φ, for the PU to be estimated that size is 4 × 4 and 8 × 8, then by 8 before arrangement
Predictive mode adds Φ.
Step (6) specifically includes：
Rate distortion costs minimum is chosen in the candidate pattern set Φ obtained using rate-distortion optimization technology from step (5)
Optimal intra prediction mode of the candidate pattern as PU to be estimated, complete PU to be estimated Intra prediction mode selection.
Claims (4)
1. a kind of HEVC Adaptive Mode Selection Method for Intra-Prediction, it is characterised in that described system of selection comprises the following steps：
(1) PU to be estimated is inputted, establishes actually available intra prediction mode set：
It is adjacent according to the space that the adjacent reconstruction pixel in the existing spaces of PU to be estimated and each HEVC intra prediction modes need
Pixel is rebuild, all actually available intra prediction modes is chosen for PU to be estimated, forms set omega；
(2) calculate all pixels in PU to be estimated be different from direction spatial neighborhood pixels absolute difference and：
When the angle predictive mode that numbering is 18 in Ω be present, i.e., PU to be estimated can be used and diagonally carried out toward lower right
The angle predictive mode of prediction, then calculate in PU to be estimated the absolute difference of all pixels and its upper left side adjacent pixel and
SADLU, as shown in formula (1)：
<mrow>
<msub>
<mi>SAD</mi>
<mrow>
<mi>L</mi>
<mi>U</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>x</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mo>|</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>-</mo>
<mn>1</mn>
<mo>,</mo>
<mi>y</mi>
<mo>-</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (1), PU to be estimated size is N × N (N=4,8,16,32,64), p (x, y) be in PU to be estimated coordinate for (x,
Y) pixel value of pixel, wherein x are horizontal coordinate, and y is vertical coordinate, and their value is more than or equal to 0 in PU to be estimated
And the integer less than N, coordinate is the upper left side that the pixel of (x-1, y-1) is located at the pixel that coordinate is (x, y)；
When the angle predictive mode that numbering is 26 in Ω be present, i.e., PU to be estimated can use what vertically downward direction was predicted
Angle predictive mode, then calculate all pixels and the absolute difference and SAD of its top adjacent pixel in PU to be estimatedU, such as formula
(2) shown in：
<mrow>
<msub>
<mi>SAD</mi>
<mi>U</mi>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>x</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mo>|</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>-</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (2), PU to be estimated size is N × N (N=4,8,16,32,64), p (x, y) be in PU to be estimated coordinate for (x,
Y) pixel value of pixel, wherein x are horizontal coordinate, and y is vertical coordinate, and their value is more than or equal to 0 in PU to be estimated
And the integer less than N, coordinate is the surface that the pixel of (x, y-1) is located at the pixel that coordinate is (x, y)；
When the angle predictive mode that numbering is 34 in Ω be present, i.e., PU to be estimated can use diagonally lower left progress pre-
The angle predictive mode of survey, then calculate in PU to be estimated the absolute difference of all pixels and its upper right side adjacent pixel and
SADRU, as shown in formula (3)：
<mrow>
<msub>
<mi>SAD</mi>
<mrow>
<mi>R</mi>
<mi>U</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>x</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mo>|</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>+</mo>
<mn>1</mn>
<mo>,</mo>
<mi>y</mi>
<mo>-</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (3), PU to be estimated size is N × N (N=4,8,16,32,64), p (x, y) be in PU to be estimated coordinate for (x,
Y) pixel value of pixel, wherein x are horizontal coordinate, and y is vertical coordinate, and their value is more than or equal to 0 in PU to be estimated
And the integer less than N, coordinate is the upper right side that the pixel of (x+1, y-1) is located at the pixel that coordinate is (x, y)；
When the angle predictive mode that numbering is 10 in Ω be present, i.e., PU to be estimated can use what horizontal right direction was predicted
Angle predictive mode, then calculate all pixels and the absolute difference and SAD of its left adjacent pixel in PU to be estimatedL, such as formula
(4) shown in：
<mrow>
<msub>
<mi>SAD</mi>
<mi>L</mi>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>x</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mo>|</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>-</mo>
<mn>1</mn>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (4), PU to be estimated size is N × N (N=4,8,16,32,64), p (x, y) be in PU to be estimated coordinate for (x,
Y) pixel value of pixel, wherein x are horizontal coordinate, and y is vertical coordinate, and their value is more than or equal to 0 in PU to be estimated
And the integer less than N, coordinate is the left that the pixel of (x-1, y) is located at the pixel that coordinate is (x, y)；
When the angle predictive mode that numbering is 2 in Ω be present, i.e., PU to be estimated can use diagonally upper right progress pre-
The angle predictive mode of survey, then calculate in PU to be estimated the absolute difference of all pixels and its lower left adjacent pixel and
SADLB, as shown in formula (5)：
<mrow>
<msub>
<mi>SAD</mi>
<mrow>
<mi>L</mi>
<mi>B</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>x</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>y</mi>
<mo>=</mo>
<mn>0</mn>
</mrow>
<mrow>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</munderover>
<mo>|</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>-</mo>
<mn>1</mn>
<mo>,</mo>
<mi>y</mi>
<mo>+</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>|</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (5), PU to be estimated size is N × N (N=4,8,16,32,64), p (x, y) be in PU to be estimated coordinate for (x,
Y) pixel value of pixel, wherein x are horizontal coordinate, and y is vertical coordinate, and their value is more than or equal to 0 in PU to be estimated
And the integer less than N, coordinate is the lower left that the pixel of (x-1, y+1) is located at the pixel that coordinate is (x, y)；
(3) according to the absolute difference of different directions spatial neighborhood pixels and the grain direction characteristic for judging PU to be estimated：
Step selection is carried out according to the absolute difference being calculated from step (2) and SAD number first：If step (2) is counted
Calculation obtains SAD number less than 3, then performs step (5)；Otherwise the SAD first step (2) being calculated is arranged from small to large
Row, classify to PU to be estimated grain direction characteristic；
(4) thick level pattern search scope is determined according to grain direction characteristic；
(5) rate-distortion optimization candidate pattern set is established according to thick level pattern search scope and Ω；
(6) optimal intra prediction mode is chosen：
The minimum candidate's mould of rate distortion costs is chosen in the candidate pattern set obtained using rate-distortion optimization technology from step (5)
Optimal intra prediction mode of the formula as PU to be estimated, complete PU to be estimated Intra prediction mode selection.
A kind of 2. HEVC Adaptive Mode Selection Method for Intra-Prediction as claimed in claim 1, it is characterised in that described step
(3) in, if first three minimum SAD is followed successively by SADMIN-0、SADMIN-1And SADMIN-2, it is right further according to these three minimum SAD
PU to be estimated textural characteristics are classified, as shown in formula (6):
<mrow>
<mi>C</mi>
<mi>l</mi>
<mi>a</mi>
<mi>s</mi>
<mi>s</mi>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mn>0</mn>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>i</mi>
<mi>f</mi>
<mi> </mi>
<msub>
<mi>SAD</mi>
<mrow>
<mi>M</mi>
<mi>I</mi>
<mi>N</mi>
<mo>-</mo>
<mn>0</mn>
</mrow>
</msub>
<mo>></mo>
<mi>&alpha;</mi>
<mo>&times;</mo>
<msub>
<mi>SAD</mi>
<mrow>
<mi>M</mi>
<mi>I</mi>
<mi>N</mi>
<mo>-</mo>
<mn>2</mn>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mn>1</mn>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>e</mi>
<mi>l</mi>
<mi>s</mi>
<mi>e</mi>
<mi> </mi>
<mi>i</mi>
<mi>f</mi>
<mi> </mi>
<msub>
<mi>SAD</mi>
<mrow>
<mi>M</mi>
<mi>I</mi>
<mi>N</mi>
<mo>-</mo>
<mn>0</mn>
</mrow>
</msub>
<mo><</mo>
<mi>&beta;</mi>
<mo>&times;</mo>
<msub>
<mi>SAD</mi>
<mrow>
<mi>M</mi>
<mi>I</mi>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mn>2</mn>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>e</mi>
<mi>l</mi>
<mi>s</mi>
<mi>e</mi>
<mi> </mi>
<mi>i</mi>
<mi>f</mi>
<mi> </mi>
<msub>
<mi>SAD</mi>
<mrow>
<mi>M</mi>
<mi>I</mi>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msub>
<mo><</mo>
<mi>&gamma;</mi>
<mo>&times;</mo>
<msub>
<mi>SAD</mi>
<mrow>
<mi>M</mi>
<mi>I</mi>
<mi>N</mi>
<mo>-</mo>
<mn>2</mn>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mn>3</mn>
<mo>,</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>o</mi>
<mi>t</mi>
<mi>h</mi>
<mi>e</mi>
<mi>r</mi>
<mi>s</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula (6), Class represents PU to be estimated texture classification, is worth and represents that PU to be estimated texture is relatively flat for 0, is worth for 1
Represent that significantly horizontal, vertical or diagonal is presented in PU to be estimated texture, the texture being worth for 2 expression PU to be estimated is in
Existing other angle directions, it is worth and represents that PU to be estimated texture is complicated for 3, parameter alpha, β and γ are used to adjust SADMIN-i(i=0,1,
2) relation between, wherein α are set to 0.9~1.0, β and γ is set to 0.6~1.0；
Then PU texture classification Class and the SAD relations being calculated by formula (6), obtain PU grain directions characteristic to be estimated,
As shown in table 1,
The PU grain directions characteristic to be estimated of table 1
Wherein 0 degree of direction refers to horizontally right direction, and pi/2 direction refers to along vertically downward direction, and the direction of π/4 refers to along bottom right
45 degree of directions, the direction of-π/4 refer to along 45 degree of directions of upper right, and the direction of 3 π/4 refers to along 45 degree of lower-left direction.
A kind of 3. HEVC Adaptive Mode Selection Method for Intra-Prediction as claimed in claim 1, it is characterised in that the step
(4) in, the PU to be estimated obtained according to step (3) grain direction characteristic, the predictive mode species of candidate is reduced, after adjustment
Predictive mode forms thick level pattern search scope S, as shown in table 2 below,
Predictive mode in the S of table 2
Predictive mode in wherein S is set according to PU to be estimated grain direction characteristic.
A kind of 4. HEVC Adaptive Mode Selection Method for Intra-Prediction as claimed in claim 1, it is characterised in that in step (5),
SATD cost pattern search scopes Ψ is determined first：If going to current procedures from step (4), Ψ is that step (4) obtains
Thick level pattern search scope S and step (1) obtain Ω common factor, if going to current procedures from step (3), direct general
Ω is assigned to Ψ；Then the HEVC intra predictions of each predictive mode in Ψ are calculated, then calculate the SATD costs of prediction residual；
Each predictive mode is ranked up then according to the orders of SATD costs J from small to large, further according to the predictive mode after sequence
Establish rate-distortion optimization candidate pattern set Φ：When the predictive mode for being arranged in the 1st is DC patterns or Planar patterns, then only
The predictive mode of 1 before arrangement is added into Φ；When the predictive mode for being arranged in the 1st is angle mode and the prediction mould of the 2nd
Formula is DC patterns or Planar patterns, then the predictive mode of 2 before arrangement only is added into Φ；When the prediction mould for being arranged in front 2
Formula is adjacent angle mode, then the predictive mode of 2 before arrangement only is added into Φ；When the predictive mode for being arranged in front 2 is
Non-conterminous angle mode, then the predictive mode of 2 before arrangement is first added into Φ, then by the adjacent angle of 2 kinds of predictive modes
Pattern adds Φ；In other cases, for the PU to be estimated that size is 16 × 16,32 × 32 and 64 × 64, then by before arrangement 3
The predictive mode of position adds Φ, for the PU to be estimated that size is 4 × 4 and 8 × 8, then adds the predictive mode of 8 before arrangement
Φ。
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