CN108650511A - The monitor video rate-distortion optimal coding method propagated based on background distortions - Google Patents

The monitor video rate-distortion optimal coding method propagated based on background distortions Download PDF

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CN108650511A
CN108650511A CN201810458872.0A CN201810458872A CN108650511A CN 108650511 A CN108650511 A CN 108650511A CN 201810458872 A CN201810458872 A CN 201810458872A CN 108650511 A CN108650511 A CN 108650511A
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frame
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CN108650511B (en
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熊健
路丽果
桂冠
杨洁
范山岗
潘金秋
华文韬
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Nanjing Post and Telecommunication University
Nanjing University of Posts and Telecommunications
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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
    • H04N19/169—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
    • H04N19/17—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 an image region, e.g. an object
    • H04N19/176—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 an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/147—Data rate or code amount at the encoder output according to rate distortion criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/149—Data rate or code amount at the encoder output by estimating the code amount by means of a model, e.g. mathematical model or statistical model
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/189—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding
    • H04N19/19—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the adaptation method, adaptation tool or adaptation type used for the adaptive coding using optimisation based on Lagrange multipliers

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Abstract

The invention discloses a kind of monitor video rate-distortion optimal coding methods propagated based on background distortions, encoding block is divided into background block and foreground blocks first, it builds background block and is distorted propagation model, global rate-distortion optimization is carried out based on background block distortion propagation model, obtain the parameter of global rate-distortion optimization, background block is marked using mask, mask is reversibly encoded, based on asymmetric quantization parameter to background block coding, background block mask and asymmetric quantization parameter deviant are decoded in decoding end, realize the reconstruct to background block.The present invention realizes the raising of monitored video compression performance and code efficiency, solves background and foreground and interacts in coding the technical problem for causing code efficiency low.

Description

The monitor video rate-distortion optimal coding method propagated based on background distortions
Technical field
The invention belongs to differentiate rate-distortion optimization field, and in particular to a kind of monitor video rate propagated based on background distortions Aberration optimizing coding method.
Background technology
With the fast development of multimedia technology and becoming increasingly popular for video monitoring equipment, video monitoring is intuitive with it, accurate Really, it enriches with the information content in time and is widely used in the occasions such as safety in production, wisdom traffic, safe city, monitor video number Volatile growth is showed according to amount.Currently, the video monitoring camera quantity in Chinese large-sized city is usually all at hundreds thousand of More than, the mounted camera in National urban alreadys exceed 20,000,000.Video monitoring has become after DTV, video council Another great Video Applications after view, and have become " scale of construction " maximum Video Applications system.In face of a large amount of How the magnanimity monitor video of camera acquisition and high carrying cost, effectively encode it compression and had become currently The significant challenge that field of video monitoring faces.Monitored video compression coding techniques is the links such as its storage, transmission, analysis and identification Premise, be the core technology of video surveillance applications.
Current video compression technology has HEVC, H.264/AVC, these technologies have been all made of a large amount of coding mode and volume Code parameter.How optimal coding mode and parameter are chosen, and the technology to reach optimal compression performance is referred to as rate-distortion optimization. The technology is based on Shannon rate and is distorted coding theory, to spend bit few as possible, obtain high as possible video quality, reach rate The optimal purpose of distortion performance.In practical applications, rate-distortion optimization technology is skill most basic, most crucial in Video coding Art, almost all of video encoding optimization are basic criterion with rate-distortion optimization.In view of the important of monitored video compression technology Property and rate-distortion optimization technology in video compression key, the rate-distortion optimization technology towards monitor video coding grind Study carefully the key as video multimedia application.
The key problem of Video coding rate-distortion optimization is, under the limitation of bit consumption, how to minimize Video coding Distortion, be expressed as minD, s.t.R ＜ Rc, wherein D expression distortions, R expression bit consumptions, RcIndicate maximal bit consumption, S.t. " in the following conditions " are indicated, the formula meaning is in the case where consuming no more than certain maximal bit so that distortion reaches It is minimum.
Sullivan et al. is proposed using lagrange's method of multipliers, and essentially, this method is bright using glug Bit consumption is mapped to distortion by day multiplier, and then constrained optimization problem is converted into unconfined optimization problem.The party Method is widely used in existing coding techniques.However, on the one hand, lagrange's method of multipliers is based on Shannon's theorems in high code Approximation under the conditions of rate, shows the deficiency of performance in Low Bit-rate Coding application, and a large amount of background area in monitor video It is encoded using extremely low bit number, therefore this method is not particularly suited for the background area of monitor video；On the other hand, glug Bright day multiplier is to be set to function about quantization step according to experiment statistics, and value is unrelated with incoming video signal.No Same parameter will lead to different coding results, the compression obtained for diversified video content in practical application, this method Performance is insufficient.
Presently, there are the problem of：
Problem 1：Lack the research for monitor video background area and foreground area rate-distortion characteristic differentiation, existing side Method is dedicated to building the adaptive model based on lagrange's method of multipliers, and has ignored the model and be not particularly suited for the monitor video back of the body Scene area Low Bit-rate Coding lacks the introducing of Classified optimization thinking.
Problem 2：Lack and disturbing factor of the background block in the estimation of adaptive rate distortion model is studied, existing method is usual The coding information of background block is used for the estimation of foreground blocks adaptive model, has ignored the interference effect of background block coding information, It can not ensure the accuracy of foreground blocks adaptive rate distortion model.
Problem 3：Lack the global Distortion Optimization model established to background block distortion propagation characteristic, existing method has ignored The extremely strong propagation characteristic that monitor video background block has lacks the thinking of global rate-distortion optimization.
Invention content
It is an object of the invention to solve the above problems, a kind of monitor video rate distortion propagated based on background distortions is proposed Optimized Coding realizes the raising of monitored video compression performance and code efficiency, and it is mutual in coding to solve background and foreground Influence the technical problem for causing code efficiency low.
The present invention adopts the following technical scheme that, a kind of monitor video rate-distortion optimal coding side propagated based on background distortions Method is as follows：
1) encoding block is divided into background block and foreground blocks；
2) structure background block is distorted propagation model；
3) it is based on background block distortion propagation model and carries out global rate-distortion optimization, obtain the parameter of global rate-distortion optimization；
4) it utilizes mask to mark background block, mask is reversibly encoded；
5) asymmetric quantization parameter is based on to background block coding；
6) background block mask and quantization parameter (quantization parameter, QP) deviant are carried out in decoding end The reconstruct to background block is realized in decoding.
Preferably, encoding block is divided into background block and foreground blocks in step 1), classification and Detection specially is carried out to background block, Obtain the continuous background block of K frames in time domain；
Preferably, structure background block distortion propagation model is specially in step 2)：
It is distorted propagation model based on static background structure background block：For the background block of continuous K frames in time domain, background block is Square, the distortion of the i-th frame background block and bit consumption are respectively DiAnd Ri, wherein i=1,2 ..., K, pi,jIndicate the i-th frame figure Picture, the source pixel value that coordinate position is j,It indicates the i-th frame image, the decoded pixel value of pixel that coordinate position is j, compiles The source pixel value of the same coordinate position of each frame background block is identical during code, i.e. pi,j=pi-1,j=...=p1,j, pi-1,jWith p1,jThe source pixel value that the coordinate position of the (i-1)-th frame image is j and the source pixel that the 1st frame image coordinate location is j are indicated respectively Value, the coordinate position j=1,2 ..., N of pixel2, N is the length of side of background block；It is encoded using SKIP patterns, i.e. same position Reconstructed pixel have it is propagated, WithThe seat of the (i-1)-th frame image is indicated respectively The decoded pixel value of pixel that mark is set to the decoded pixel value of pixel of j and the 1st frame image coordinate location is j, the i-th frame The distortion D of background blockiThere is following relationship：
Wherein, D1Indicate the distortion of first frame background block.
Preferably, global rate-distortion optimization is carried out in step 3), obtain the parameter of global rate-distortion optimization the specific steps are：
31) in time domain continuous K frames background block, the distortion of the i-th frame background block and bit consumption are respectively DiAnd Ri, wherein i =1,2 ..., K are distorted the rate distortion costs that propagation model target is the background block entirety for minimizing continuous K frames based on background block, The global rate-distortion optimization formula of background block is
Wherein λcFor the Lagrange's multiplier of rate-distortion optimization, D1And R1Distortion and the ratio of first frame background block are indicated respectively Spy's consumption；
32) it is based on background block and is distorted propagation model, the global rate-distortion optimization formula of background block is rewritten as
Respectively to R1And RiLocal derviation is sought, obtains Lagrange's multiplier into following relationship：
Wherein λ1Indicate the Lagrange's multiplier of first frame background block, λiIndicate the Lagrange's multiplier of the i-th frame background block, The Lagrange's multiplier of subsequent frame is K times of first frame Lagrange's multiplier, i.e. λi=K λ1。
Preferably, background block is marked using mask in step 4), mask is reversibly encoded, is specially being compiled Code end using K frames as a cycle, each period is marked background block using a mask, using arithmetic coding to mask into Row coding.
Preferably, it is specially to background block coding based on asymmetric quantization parameter in step 5)：
It is in power function relationship based on R- λ models, between bit consumption R and lagrangian multiplier：
R=α λβ
Wherein α and β is R- λ model parameters, keeps total bit consumption of current background block constant, obtains
α·λ1 β+(K-1)α·(K·λ1)β=K α λc β
Wherein λcFor the Lagrange's multiplier of rate-distortion optimization, K is continuous K frame background blocks in time domain, is obtained
Wherein, λ1Indicate the Lagrange's multiplier of first frame background block；
Quantization parameter is
QP=4.2005ln (λ)+13.7122
By λ1And λiAbove-mentioned formula is substituted into respectively, obtains the quantization parameter of each frame, and using corresponding quantization parameter to covering All background blocks of membrane marker are encoded.
The reached advantageous effect of invention：The present invention proposes that a kind of monitor video rate distortion propagated based on background distortions is excellent Change coding method, realize the raising of monitored video compression performance and code efficiency, solves background and the foreground mutual shadow in coding The technical problem that pilot causes code efficiency low；Encoding block classification and Detection and a variety of rate-distortion optimization models are combined by the present invention, It is optimized for encoding block rate-distortion characteristic difference, there is important meaning for promoting monitored video compression performance and code efficiency Justice, present invention could apply to the multiple fields of Video coding, including monitor video and video conference etc..
Description of the drawings
Fig. 1 is the background block overall situation Rate-distortion optimization method flow chart based on background distortions propagation model of the present invention；
Fig. 2 is monitor video background block distortion propagation model schematic diagram.
Specific implementation mode
Below according to attached drawing and technical scheme of the present invention is further elaborated in conjunction with the embodiments.
The present invention adopts the following technical scheme that, a kind of monitor video rate-distortion optimal coding side propagated based on background distortions Method, the present invention realize that Fig. 1 is the flow chart of the present invention, tool on HM16.0 (HEVC officials test software) experiment porch Steps are as follows for body：
1) encoding block is divided into background block and foreground blocks；
Encoding block is divided into background block and foreground blocks in step 1), classification and Detection specially is carried out to background block, when obtaining The continuous background block of K frames on domain；By the background uniformity of monitor video, it is reasonable to predict this position encoded piece in follow-up several frames Also it is background block.
2) structure distortion propagation model；
Structure background block distortion propagation model is specially in step 2)：
It is distorted propagation model based on static background structure background block：For the background block of continuous K frames in time domain, background block is Square, the distortion of the i-th frame background block and bit consumption are respectively DiAnd Ri, wherein i=1,2 ..., K, pi,jIndicate the i-th frame figure Picture, the source pixel value that coordinate position is j,It indicates the i-th frame image, the decoded pixel value of pixel that coordinate position is j, compiles The source pixel value of the same coordinate position of each frame background block is identical during code, i.e. pi,j=pi-1,j=...=p1,j, pi-1,jWith p1,jThe source pixel value that the coordinate position of the (i-1)-th frame image is j and the source pixel that the 1st frame image coordinate location is j are indicated respectively Value, the coordinate position j=1,2 ..., N of pixel2, N is the length of side of background block；It is encoded using SKIP patterns, i.e. same position Reconstructed pixel have it is propagated, WithThe seat of the (i-1)-th frame image is indicated respectively The decoded pixel value of pixel that mark is set to the decoded pixel value of pixel of j and the 1st frame image coordinate location is j, the i-th frame The distortion D of background blockiThere is following relationship：
Wherein, D1Indicate the distortion of first frame background block.
3) as shown in Fig. 2, horizontal axis presentation code bit consumption, the longitudinal axis indicates corresponding coding distortion, and each point indicates in figure By under different coding Parameter Conditions coded-bit consumption and coding distortion.Global rate is carried out based on background block distortion propagation model Aberration optimizing obtains the parameter of global rate-distortion optimization, the specific steps are：
31) in time domain continuous K frames background block, the distortion of the i-th frame background block and bit consumption are respectively DiAnd Ri, wherein i =1,2 ..., K carry out the rate distortion costs that global rate-distortion optimization target is the background block entirety for minimizing continuous K frames, background The global rate-distortion optimization formula of block is
Wherein λcFor the Lagrange's multiplier of rate-distortion optimization, D1And R1Distortion and the ratio of first frame background block are indicated respectively Spy's consumption；
32) it is based on background block and is distorted propagation model, the global rate-distortion optimization formula of background block is rewritten as
Respectively to R1And RiLocal derviation is sought, obtains Lagrange's multiplier into following relationship：
Wherein λ1Indicate the Lagrange's multiplier of first frame background block, λiIndicate the Lagrange's multiplier of the i-th frame background block, The Lagrange's multiplier of subsequent frame is K times of first frame Lagrange's multiplier, i.e. λi=K λ1。
4) background block is marked using mask, mask is reversibly encoded, specially coding side with K frames be one A period, each period are marked background block using a mask, are encoded to mask using arithmetic coding.
5) asymmetric quantization parameter is based on to background block coding；
To keep total coding bit in smaller range to change, need to be chosen according to above-mentioned relation in actual coding corresponding Quantization parameter calculate the Lagrange's multiplier after adjustment, step using the relationship between coded-bit and Lagrange's multiplier It is rapid 5) in based on asymmetric quantization parameter be specially to background block coding：
It is in power function relationship based on R- λ models, between bit consumption R and lagrangian multiplier：
R=α λβ
Wherein α and β is R- λ model parameters, keeps total bit consumption of current background block constant, obtains
α·λ1 β+(K-1)α·(K·λ1)β=K α λc β
Wherein λcFor the Lagrange's multiplier of rate-distortion optimization, K is continuous K frame background blocks in time domain, is obtained
Wherein, λ1Indicate the Lagrange's multiplier of first frame background block；
Quantization parameter is
QP=4.2005ln (λ)+13.7122
By λ1And λiAbove-mentioned formula is substituted into respectively, obtains the quantization parameter of each frame, and using corresponding quantization parameter to covering All background blocks of membrane marker are encoded.When K values are larger, λ1And λiDifference is larger, the quantization ginseng of first frame and subsequent frame Several value difference is larger, referred to as asymmetric quantization parameter coding.
6) background block mask and quantization parameter QP deviants are decoded in decoding end, realize the reconstruct to background block.

Claims (6)

1. the monitor video rate-distortion optimal coding method propagated based on background distortions, which is characterized in that include the following steps：
1) encoding block is divided into background block and foreground blocks；
2) structure background block is distorted propagation model；
3) it is based on background block distortion propagation model and carries out global rate-distortion optimization, obtain the parameter of global rate-distortion optimization；
4) it utilizes mask to mark background block, mask is reversibly encoded；
5) asymmetric quantization parameter is based on to background block coding；
6) background block mask and asymmetric quantization parameter deviant are decoded in decoding end, realize the reconstruct to background block.
2. the monitor video rate-distortion optimal coding method according to claim 1 propagated based on background distortions, feature It is, encoding block is divided into background block and foreground blocks in step 1), classification and Detection specially is carried out to background block, is obtained in time domain The continuous background block of K frames.
3. the monitor video rate-distortion optimal coding method according to claim 1 propagated based on background distortions, feature It is, structure background block distortion propagation model is specially in step 2)：
It is distorted propagation model based on static background structure background block：For the background block of continuous K frames in time domain, background block is pros Shape, the distortion of the i-th frame background block and bit consumption are respectively DiAnd Ri, wherein i=1,2 ..., K, pi,jIt indicates the i-th frame image, sit Mark is set to the source pixel value of j,Indicate the i-th frame image, the decoded pixel value of pixel that coordinate position is j, cataloged procedure In each frame background block same coordinate position source pixel value it is identical, i.e. pi,j=pi-1,j=...=p1,j, pi-1,jAnd p1,jRespectively Indicate the source pixel value that the coordinate position for the source pixel value and the 1st frame image that the coordinate position of the (i-1)-th frame image is j is j, pixel Coordinate position j=1,2 ..., N2, N is the length of side of background block；It is encoded using SKIP patterns, i.e., WithThe decoded pixel value of pixel and that the coordinate position of the (i-1)-th frame image is j is indicated respectively The coordinate position of 1 frame image is the decoded pixel value of pixel of j, the distortion D of the i-th frame background blockiThere is following relationship：
Wherein, D1Indicate the distortion of first frame background block.
4. the monitor video rate-distortion optimal coding method according to claim 1 propagated based on background distortions, feature Be, global rate-distortion optimization carried out in step 3), obtain the parameter of global rate-distortion optimization the specific steps are：
31) in time domain continuous K frames background block, the distortion of the i-th frame background block and bit consumption are respectively DiAnd Ri, wherein i=1, 2 ..., K carry out the rate distortion costs that global rate-distortion optimization target is the background block entirety for minimizing continuous K frames, background block Global rate-distortion optimization formula is
Wherein λcFor the Lagrange's multiplier of rate-distortion optimization, D1And R1Indicate that the distortion of first frame background block and bit disappear respectively Consumption；
32) it is based on background block and is distorted propagation model, the global rate-distortion optimization formula of background block is rewritten as
Respectively to R1And RiLocal derviation is sought, obtains Lagrange's multiplier into following relationship：
Wherein λ1Indicate the Lagrange's multiplier of first frame background block, λiIndicate the Lagrange's multiplier of the i-th frame background block, subsequently The Lagrange's multiplier of frame is K times of first frame Lagrange's multiplier, i.e. λi=K λ1。
5. the monitor video rate-distortion optimal coding method according to claim 1 propagated based on background distortions, feature It is, background block is marked using mask in step 4), mask is reversibly encoded, specially in coding side with K frames For a cycle, each period is marked background block using a mask, is encoded to mask using arithmetic coding.
6. the monitor video rate-distortion optimal coding method according to claim 1 propagated based on background distortions, feature It is, is specially to background block coding based on asymmetric quantization parameter in step 5)：
It is in power function relationship based on R- λ models, between bit consumption R and lagrangian multiplier：
R=α λβ
Wherein α and β is R- λ model parameters, keeps total bit consumption of current background block constant, obtains
α·λ1 β+(K-1)α·(K·λ1)β=K α λc β
Wherein λcFor the Lagrange's multiplier of rate-distortion optimization, K is continuous K frame background blocks in time domain, is obtained
Wherein, λ1Indicate the Lagrange's multiplier of first frame background block；
Quantization parameter is
QP=4.2005ln (λ)+13.7122
By λ1And λiAbove-mentioned formula is substituted into respectively, obtains the quantization parameter of each frame, and using corresponding quantization parameter to mask mark All background blocks of note are encoded.
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