CN108366256A - A kind of HEVC intra prediction modes quickly select system and method - Google Patents
A kind of HEVC intra prediction modes quickly select system and method Download PDFInfo
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- 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
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- 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
- H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
- H04N19/51—Motion estimation or motion compensation
- H04N19/567—Motion estimation based on rate distortion criteria
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- 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
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- 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
- H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
Abstract
The present invention proposes a kind of HEVC intra prediction modes and quickly selects system and method, the complexity for reducing the selection of HEVC intra-prediction code modes；System includes five modules, and MPM mode decision modules are that current prediction block determines three MPM prediction modes；All prediction directions are divided into three regions by mode region division module；Pattern direction matching module obtains high-confidence forecast mode candidate list；Rate distortion costs computing module calculates the RDcost of each pattern in high-confidence forecast mode candidate list, obtains RDcost set；Optimization model chooses module and RDcost is gathered descending sort, and it is optimal prediction modes to choose the corresponding pattern of minimum RDcost values, and the present invention has the characteristics that the intraframe predictive coding that code efficiency height and precision of prediction are high, can be used in HEVC video standards.
Description
Technical field
The invention belongs to digital signal processing technique field, more particularly to a kind of HEVC intra prediction modes quickly select be
System and method, the intraframe predictive coding that can be used in HEVC video standards.
Background technology
HEVC is a kind of new video compression standard, is used for substitute H.264/AVC coding standard, on January 26th, 2013,
HEVC formally becomes international standard.As video encoding standard of new generation, (H.265) HEVC still falls within prediction plus converts mixed
Close coding framework.However, relative to H.264, H.265 there is revolutionary variation at many aspects.
In H.265, the size of macro block is extended to 64 × 64 from 16 × 16 H.264, treats coded image successively
Carry out predictive coding, transition coding and entropy coding.Wherein predictive coding needs to select best coding unit CU, and chooses CU
In each predicting unit PU prediction mode, the prediction mode of PU shares 35 kinds, including Planar patterns (0 pattern), DC patterns
(1 pattern) and 33 kinds of angle prediction modes.
During HEVC predictive codings, coding unit CU is first chosen, is then predicting unit PU, that is, current prediction block choosing
Take optimal prediction modes.Traditional is in the technology that predicting unit PU chooses optimal prediction modes, and MPM mode decision modules are to work as
Preceding prediction block determines that three can become the highest MPM prediction modes of current prediction block optimal prediction modes probability, prediction mode
Spider module is by traversing 35 kinds of prediction modes and calculating the absolute error and SATD of each pattern, to obtain high-confidence forecast mould
Formula candidate list, rate distortion costs computing module carry out the list of high-confidence forecast mode candidate and three MPM prediction modes whole
Conjunction obtains optimal prediction modes list, and calculates the rate distortion costs RDcost of each pattern in optimal prediction modes list,
Cost RDcost set is obtained, then selects the corresponding prediction mode of minimum value from cost RDcost set, it is as current pre-
Survey the prediction mode of block.
Each coding unit CU can be divided into the predicting unit PU of several form in HEVC, when each predicting unit
When PU is as current prediction block, if selection optimal prediction modes will traverse 35 kinds of prediction modes one by one, optimum prediction can be caused
The complexity that pattern is chosen is very high, greatly reduces the code efficiency of HEVC.
Invention content
It is an object of the invention to overcome the problems of the above-mentioned prior art, a kind of HEVC intra prediction modes are provided
Quickly selection system and method, the complexity for reducing the selection of HEVC intra-prediction code modes.
To achieve the above object, the technical solution that the present invention takes is：
A kind of HEVC intra prediction modes quickly select system, including the distortion of sequentially connected MPM mode decision modules, rate
Cost computing module and optimization model choose module, wherein：
The MPM mode decision modules, for for current prediction block determine three can become current prediction block it is optimal pre-
Survey the highest MPM prediction modes of model probabilities；
The rate distortion costs computing module for obtaining optimization model candidate collection, and calculates optimization model candidate
The rate distortion costs RDcost of each pattern in set, to obtain cost RDcost set；
The optimal prediction modes choose module, for carrying out descending sort to cost RDcost set, and choose minimum
Cost RDcost, to obtain the optimal prediction modes of current prediction block；
Further include sequentially connected mode region division module and pattern direction matching module, wherein：
The mode region division module is drawn for carrying out region to 33 kinds of angle prediction modes in HEVC by direction
Point；
Pattern direction matching module, on the left of current prediction block for being obtained using MPM mode decision modules and
The prediction mode of lateral mass matches current prediction block in mode region division module three obtained region, into line direction to obtain
Take high-confidence forecast mode candidate list.
A kind of method that HEVC intra prediction modes quickly select, includes the following steps：
(1) MPM mode decision modules determine three MPM prediction modes：
First prediction mode of MPM prediction modes is denoted as ModeA, the second prediction mode by (1a) MPM mode decision modules
It is denoted as ModeB, third prediction mode is denoted as ModeC, and the prediction mode value of the left side prediction block of current prediction block is assigned to
The prediction mode value of ModeA, upside prediction block are assigned to ModeB；
(1b) MPM mode decision modules judge whether ModeA and ModeB is equal, if so, when ModeA is 0 or 1, it will
Any two value is assigned to ModeB and ModeC respectively in 0,1 and 26, will be with when ModeA is any one value in 2 to 34
Two adjacent ModeA angle prediction modes are assigned to ModeB and ModeC respectively, otherwise, by ModeC be set as 0,1 or
26, and do not repeated with ModeA and ModeB；
(2) mode region division module carries out mode region division to 33 kinds of angle prediction modes in HEVC, obtains three
A estimation range：
33 kinds of angle prediction modes in HEVC are divided into the first estimation range Area1, by mode region division module
Two estimation range Area2 and third estimation range Area3, and the prediction mode sum that each region includes is odd number；
(3) pattern direction matching module obtains high-confidence forecast mode candidate list：
(3a) pattern direction matching module judges whether ModeA and ModeB belongs to tri- areas Area1, Area2 and Area3
One in domain, if so, using the prediction mode between ModeA and ModeB as high-confidence forecast mode candidate list, otherwise,
Execute step (3b)；
(3b) pattern direction matching module setting matching section, and the left side endpoint for matching section is denoted as left end point
Ref1, right side endpoint are denoted as right endpoint ref2, and centre position is denoted as intermediate point Area (n) _ ref, and wherein n represents prediction mode
Value, and 2≤n≤34；
ModeA is assigned to ref1 by (3c) pattern direction matching module, and ModeB is assigned to ref2, and (ref1+ref2)/2 is assigned
It is worth to Area (n) _ ref；
(3d) pattern direction matching module calculates the pattern match value MSE of Area (n) _ refref, ref1 pattern match value
MSE1With the pattern match value MSE of ref22；
(3e) pattern direction matching module judges MSE1≤MSEref≤MSE2With | ref1-ref2 | whether≤5 set up simultaneously,
If so, executing step (3g), otherwise, step (3f) is executed；
Area (n) _ ref is assigned to ref1 by (3f) pattern direction matching module, (Area (n) _ ref+ref2)/2 assignment
It is assigned to ref2 to Area (n) _ ref, ModeB, and executes step (3d)；
(3g) pattern direction matching module is using the prediction mode between ref1 and ref2 as high-confidence forecast mode candidate
List；
(4) rate distortion costs computing module obtains optimization model candidate list, and calculates every in optimization model candidate list
The rate distortion costs RDcost of kind pattern obtains cost RDcost set：
The height that three MPM prediction modes that (4a) rate distortion costs computing module determines step (1) are obtained with step (3)
Probability Forecast Model candidate list is integrated, and optimal prediction modes candidate list is obtained；
The rate that (4b) rate distortion costs computing module calculates each pattern in optimal prediction modes candidate list is distorted generation
Valence RDcost obtains cost RDcost set；
(5) optimal prediction modes choose the optimal prediction modes that module obtains current prediction block：
Optimal prediction modes choose the RDcost set that rate distortion costs computing module is calculated module and carry out descending
Sequence, and select the prediction mode corresponding to minimum cost RDcost values, the optimal prediction modes as current prediction block.
The present invention has the following advantages that compared with traditional technology：
1. the present invention, when obtaining high-confidence forecast mode candidate list, use pattern region division module first is by HEVC
In 33 kinds of prediction modes carry out region division and obtain three kinds of estimation ranges, then use pattern direction matching module and MPM moulds
The prediction mode in current prediction block left side and upper block that formula determining module determines divides mould to current prediction block in mode region
Three regions that block divides are matched into line direction, are quickly positioned and are reduced matching section and then obtain high-confidence forecast mode candidate
It is pre- to obtain high probability with the method in the prior art traversing 35 kinds of prediction modes one by one by prediction mode spider module for list
It surveys mode candidate list to compare, reduces calculation times, reduce encoder complexity, be effectively improved code efficiency.
2. the present invention when carrying out region division to 33 kinds of prediction modes in HEVC, has used mode region to divide mould
33 kinds of angle prediction modes are divided into three kinds of estimation ranges by block according to the directional dependency between each prediction mode, that is, are hung down
Histogram is to the negative offset area in positive offset area, horizontal direction positive offset area and vertical and horizontal direction, and each estimation range includes
Prediction mode sum be odd number, provide convenience for subsequent direction matching process, further improve code efficiency
3. the present invention has used pattern direction matching module when calculating pattern match value MSE, calculate current prediction block and
Two-dimentional mean square error between reference block pixel value is reduced compared to the method for calculating absolute error and SAD in conventional method
It predicts error, has the characteristics that precision of prediction higher.
Description of the drawings
Fig. 1 is the overall structure diagram of selection system of the present invention；
Fig. 2 is the implementation flow chart of selection method of the present invention.
Specific implementation mode
Below in conjunction with the drawings and specific embodiments, invention is further described in detail.
Referring to Fig.1, a kind of method that HEVC intra prediction modes quickly select, includes the following steps：
A kind of HEVC intra prediction modes quickly select system, including the distortion of sequentially connected MPM mode decision modules, rate
Cost computing module and optimization model choose module, wherein：
The MPM mode decision modules, for for current prediction block determine three can become current prediction block it is optimal pre-
Survey the highest MPM prediction modes of model probabilities；
The rate distortion costs computing module for obtaining optimization model candidate collection, and calculates optimization model candidate
The rate distortion costs RDcost of each pattern in set, to obtain cost RDcost set；
The optimal prediction modes choose module, for carrying out descending sort to cost RDcost set, and choose minimum
Cost RDcost, to obtain the optimal prediction modes of current prediction block；
Further include sequentially connected mode region division module and pattern direction matching module, wherein：
The mode region division module is drawn for carrying out region to 33 kinds of angle prediction modes in HEVC by direction
Point；
Pattern direction matching module, on the left of the current prediction block block for being obtained using MPM mode decision modules and
The prediction mode of upper block matches current prediction block in mode region division module three obtained region into line direction, with
Obtain high-confidence forecast mode candidate list.
With reference to Fig. 2, a kind of method that HEVC intra prediction modes quickly select includes the following steps：
Step 1) MPM mode decision modules determine three MPM prediction modes：
Step 1a) the first prediction mode of MPM prediction modes is denoted as ModeA by MPM mode decision modules, the second prediction mould
Formula is denoted as ModeB, and third prediction mode is denoted as ModeC, and by the prediction mode value assignment of the left side prediction block of current prediction block
To ModeA, the prediction mode value of upside prediction block is assigned to ModeB；
Step 1b) MPM mode decision modules judge whether ModeA and ModeB is equal, if so, it is 0 or 1 to work as ModeA
When, any two value in 0,1 and 26 is assigned to ModeB and ModeC respectively, when ModeA is any one value in 2 to 34,
The two angle prediction modes adjacent with ModeA are assigned to ModeB and ModeC respectively, otherwise, by ModeC be set as 0,1 or
Person 26, and are not repeated with ModeA and ModeB；
Step 2) mode region division module carries out mode region division to 33 kinds of angle prediction modes in HEVC, obtains
Three estimation ranges：
Mode region division module is according to the offset of 33 kinds of angle prediction modes in the horizontal and vertical directions in HEVC
It is worth positive and negative situation, 33 kinds of angle prediction modes is divided into vertical direction positive offset area Area1, horizontal direction positive offset area
Totally three regions, Area1 indicate to be positive offset in vertical direction to Area2 and vertical and horizontal direction negative offset area Area3
Predict that Area2 indicates the region for positive offset in the horizontal direction, passes through to current block upper right by Area1 in region
Area2 predicts that Area3 expressions are the region of negative offset on vertical and horizontal direction, are passed through to current block lower left
Area3 is predicted to current block lower right, and the prediction mode sum that each region includes is odd number, wherein Area1 includes 2
Include that 11 to 27, Area3 includes 28 to 34 to 10, Area2；
Step 3) pattern direction matching module obtains high-confidence forecast mode candidate list：
Step 3a) pattern direction matching module judges whether ModeA and ModeB belongs to Area1, Area2 and Area3 tri-
One in region, if so, using the prediction mode between ModeA and ModeB as high-confidence forecast mode candidate list, it is no
Then, step 3b is executed)；
Step 3b) pattern direction matching module setting matching section, and the left side endpoint for matching section is denoted as left end point
Ref1, right side endpoint are denoted as right endpoint ref2, and centre position is denoted as intermediate point Area (n) _ ref, and wherein n represents prediction mode
Value, and 2≤n≤34；
Step 3c) ModeA is assigned to ref1 by pattern direction matching module, and ModeB is assigned to ref2, (ref1+ref2)/
2 are assigned to Area (n) _ ref；
Step 3d) pattern direction matching module calculates the pattern match value MSE of Area (n) _ refref, ref1 pattern
With value MSE1With the pattern match value MSE of ref22, pattern match value obtained using two-dimentional mean square deviation method, the meter of two-dimentional mean square deviation
Calculating formula is：
Wherein, M and N respectively represents the width and height of current prediction block, fiAnd fi-1The picture of current block and reference block is indicated respectively
Element value, x and y indicate the horizontal component and vertical component of current block and reference block respective pixel position motion vector；
Step 3e) pattern direction matching module judges MSE1≤MSEref≤MSE2With | ref1-ref2 |≤5 whether at
It is vertical, if so, executing step (3g), otherwise, execute step (3f)；
Step 3f) Area (n) _ ref is assigned to ref1 by pattern direction matching module, and (Area (n) _ ref+ref2)/2 is assigned
It is worth and is assigned to ref2 to Area (n) _ ref, ModeB, and execute step 3d)；
Step 3g) pattern direction matching module using the prediction mode between ref1 and ref2 as high-confidence forecast pattern wait
Select list；
Step 4) rate distortion costs computing module obtains optimization model candidate list and calculates in optimization model candidate list
The rate distortion costs RDcost of each pattern obtains cost RDcost set：
Step 4a) the rate distortion costs computing module height that obtains 3 MPM prediction modes that step 1) obtains with step 3)
Probability Forecast Model candidate list is integrated, and optimal prediction modes candidate list is obtained；
Step 4b) rate distortion costs computing module calculate optimal prediction modes candidate list in each pattern rate distortion
Cost RDcost obtains cost RDcost set, wherein rate distortion costs RDcost is to be distorted generation according to rate specified in HEVC
Value definition calculates each pattern, and calculation formula is：
RDcost=Distortion+ λ × uiBits
Wherein, Distortion is that the error of the reconstruction image and original image obtained after being predicted using prediction mode is flat
Fang He, λ are Lagrange factors, and uiBits is to be predicted successively image using prediction mode, convert, quantify, entropy coding
The number of coded bits generated afterwards；
Step 5) optimal prediction modes choose the optimal prediction modes that module obtains current prediction block：
Optimal prediction modes choose the RDcost set that module obtains rate distortion costs computing module and carry out descending sort,
And select prediction mode corresponding to minimum cost RDcost values, the optimal prediction modes as current prediction block.
Above description is only example of the present invention, it is clear that for those skilled in the art, is being understood
After the content of present invention and principle, all it may be carried out in form and details without departing substantially from the principle of the invention, structure
Various modifications and variations, but these modifications and variations based on inventive concept are still in the claims of the present invention
Within.
Claims (5)
1. a kind of HEVC intra prediction modes quickly select system, including sequentially connected MPM mode decision modules, rate to be distorted generation
Valence computing module and optimization model choose module, wherein：
The MPM mode decision modules, for determining that three can become current prediction block optimum prediction mould for current prediction block
The highest MPM prediction modes of formula probability；
The rate distortion costs computing module for obtaining optimization model candidate collection, and calculates the optimization model candidate collection
In each pattern rate distortion costs RDcost, to obtain cost RDcost set；
The optimal prediction modes choose module, for carrying out descending sort to cost RDcost set, and choose minimum generation
Valence RDcost, to obtain the optimal prediction modes of current prediction block；
It is characterized in that, further include sequentially connected mode region division module and pattern direction matching module, wherein：
The mode region division module, for carrying out region division to 33 kinds of angle prediction modes in HEVC by direction；
Pattern direction matching module, the current prediction block left side for being determined using MPM mode decision modules and upper block
Prediction mode, to current prediction block three regions that mode region division module divides into line direction match, to obtain height
Probability Forecast Model candidate list.
2. a kind of method that HEVC intra prediction modes quickly select, which is characterized in that include the following steps：
(1) MPM mode decision modules determine three MPM prediction modes：
First prediction mode of MPM prediction modes is denoted as ModeA by (1a) MPM mode decision modules, and the second prediction mode is denoted as
ModeB, third prediction mode is denoted as ModeC, and the prediction mode value of the left side prediction block of current prediction block is assigned to
The prediction mode value of ModeA, upside prediction block are assigned to ModeB；
(1b) MPM mode decision modules judge whether ModeA and ModeB is equal, if so, when ModeA is 0 or 1, by 0,1
With 26 in any two value be assigned to ModeB and ModeC respectively, will be with ModeA when ModeA is any one value in 2 to 34
Two adjacent angle prediction modes are assigned to ModeB and ModeC respectively, otherwise, ModeC are set as 0,1 or 26, and with
ModeA and ModeB are not repeated；
(2) mode region division module carries out mode region division to 33 kinds of angle prediction modes in HEVC：
33 kinds of angle prediction modes in HEVC are divided into the first estimation range Area1, second in advance by mode region division module
Region Area2 and third estimation range Area3 is surveyed, and the prediction mode sum that each region includes is odd number；
(3) pattern direction matching module obtains high-confidence forecast mode candidate list：
(3a) pattern direction matching module judges whether ModeA and ModeB belongs in tri- regions Area1, Area2 and Area3
One, if so, using the prediction mode between ModeA and ModeB as high-confidence forecast mode candidate list, otherwise, execute
Step (3b)；
(3b) pattern direction matching module setting matching section, and the left side endpoint for matching section is denoted as left end point ref1, it is right
Side point is denoted as right endpoint ref2, and centre position is denoted as intermediate point Area (n) _ ref, and wherein n represents prediction mode value, and 2≤n
≤34；
ModeA is assigned to ref1 by (3c) pattern direction matching module, and ModeB is assigned to ref2, and (ref1+ref2)/2 is assigned to
Area(n)_ref；
(3d) pattern direction matching module calculates the pattern match value MSE of Area (n) _ refref, ref1 pattern match value MSE1
With the pattern match value MSE of ref22；
(3e) pattern direction matching module judges MSE1≤MSEref≤MSE2With | ref1-ref2 | whether≤5 set up simultaneously, if
It is to execute step (3g), otherwise, executes step (3f)；
Area (n) _ ref is assigned to ref1 by (3f) pattern direction matching module, and (Area (n) _ ref+ref2)/2 is assigned to
Area (n) _ ref, ModeB are assigned to ref2, and execute step (3d)；
(3g) pattern direction matching module is using the prediction mode between ref1 and ref2 as high-confidence forecast mode candidate list；
(4) rate distortion costs computing module obtains optimization model candidate list, and calculates each mould in optimization model candidate list
The rate distortion costs RDcost of formula obtains cost RDcost set：
The high probability that three MPM prediction modes that (4a) rate distortion costs computing module determines step (1) are obtained with step (3)
Prediction mode candidate list is integrated, and optimal prediction modes candidate list is obtained；
(4b) rate distortion costs computing module calculates the rate distortion costs of each pattern in optimal prediction modes candidate list
RDcost obtains cost RDcost set；
(5) optimal prediction modes choose the optimal prediction modes that module obtains current prediction block：
Optimal prediction modes choose the RDcost set that rate distortion costs computing module is calculated module and carry out descending sort,
And select prediction mode corresponding to minimum cost RDcost values, the optimal prediction modes as current prediction block.
3. a kind of method that HEVC intra prediction modes quickly select according to claim 2, it is characterised in that：Step
(2) the mode region division module described in carries out mode region division to 33 kinds of angle prediction modes in HEVC, realizes
Cheng Wei：
Mode region division module according to the deviant of 33 kinds of angle prediction modes in the horizontal and vertical directions in HEVC just
Forsake one's love condition, by 33 kinds of angle prediction modes be divided into vertical direction positive offset area Area1, horizontal direction positive offset area Area2 and
Totally three regions vertical and horizontal direction negative offset area Area3.
4. a kind of method that HEVC intra prediction modes quickly select according to claim 2, it is characterised in that：Step
The pattern match value MSE of calculating Area (n) _ ref described in (3d)ref, ref1 pattern match value MSE1With the pattern of ref2
Matching value MSE2, using two-dimentional mean square deviation method, the formula expression of two-dimentional mean square deviation is：
Wherein, M and N respectively represents the width and height of current prediction block, fiAnd fi-1The pixel value of current block and reference block is indicated respectively,
X and y indicates the horizontal component and vertical component of current block and reference block respective pixel position motion vector.
5. the method that a kind of intra prediction mode based on HEVC standard according to claim 2 quickly selects, feature
It is：The rate distortion costs RDcost for calculating each pattern in optimal prediction modes candidate list described in step (4b),
It is to be calculated each pattern according to rate distortion costs value definition specified in HEVC, calculation formula is：
RDcost=Distortion+ λ × uiBits
Wherein, Distortion is the reconstruction image obtained after being predicted using prediction mode and the square-error of original image
Lagrange factor with, λ, uiBits be image is predicted successively using prediction mode, is converted, is quantified and entropy coding after
The number of coded bits of generation.
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