CN104683804B - Parameter adaptive multidimensional bit rate control method based on video content features - Google Patents
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Abstract
The present invention relates to video decoding filed, the parameter adaptive multidimensional bit rate control method specially based on video content features.This method includes：Optimal initial code frame per second is determined according to the initial frame complexity of channel width and video sequence；The model parameter update cycle is determined according to the video of dynamic mapping, video Space-time Complexity is extracted out of current update cycle sliding window, in combination with the accuracy of current update cycle Rate Control, the length of next update cycle is determined, and multidimensional code check Controlling model parameter and coding parameter are updated；The parameter adaptive multidimensional bit rate control method of video content features proposed by the invention can effectively improve subjective quality and objective quality, particularly with the higher video sequence of Space-time Complexity better than intra-class correlation method in the world；Meanwhile it also can somewhat reduce the complexity of calculating.
Description
Technical field
It is special in particular to the bit rate control method of technical field of video coding the present invention relates to video decoding filed
It is not the parameter adaptive multidimensional bit rate control method based on video content features, can apply in Multielement integration heterogeneous network
Network, the network video coder multidimensional bit rate control method with broad range dynamic change occasion.
Background technology
As multimedia communication and the development of network technology, people are more and more extensive to the application demand of video, video letter
The life style and social development for ceasing face people play more and more important effect；Video Coding Compression Technology is that video is deposited
The premise of the links such as storage, transmission, broadcasting, it is the core technology of the applications such as DTV, video monitoring, Internet video；Code check control
Technology processed is one of most important link in video compress and transmission, and the purpose of Rate Control is in certain actual channel band
Under width, as much as possible improve Video coding reconstructed image subjective and objective quality, and be responsible for making code check caused by video encoder and
Actual channel bandwidth matches, therefore its effect in the encoder is particularly significant.
Existing bit rate control method is all based on the adjustment of quantization parameter to balance code stream, and existing method typically can only
A kind of video frequency output of credit rating is provided, this way is inadequate for the big application flexibility ratio of bandwidth fluctuation, can not be in bandwidth
Cause comprehensive video optimal quality in the case of real-time low bit- rate；Multidimensional Rate Control is exactly to be suggested under this background, more
Tie up Rate Control to organically combine the basic means for adjusting code check, traditional code check conversion (change quantization step), space are solved
The code rate adjustment means such as analysis degree (sdi video size), temporal analytical density (frame per second) combine oneself of collaboration completion video code flow
Adapt to regulation；Because each dimension size of multidimensional Rate Control determines how much be to rely on a period of time code check, in actual applications
And some grades need not be divided into advance, can effectively solve the problems, such as that SVC computation complexities and redundancy are high.
But at present, also in the starting stage, the research for also having more tool expansions needs multidimensional rate control techniques
Carry out, the development of the research of its key technology for video industry has important practical significance；Multidimensional code check controlling party at present
There are the following problems for method：(1) current main stream approach, such as Q-R-TQ etc. are to be based on whole video when calculating video content information
Information or by the fixed cycle, and the content of video is time-varying in actual applications, is obtained for the sequence for changing over time violent
Its accuracy of the model coefficient arrived is not high, is unfavorable for real-time Transmission；(2) initial being chosen in multidimensional Rate Control for frame per second plays
Important effect；If the initial frame per second chosen is excessive, will be exceeded by only encoding the bit number actually consumed after initial frame by pre- point
The target bit matched somebody with somebody, will be seldom so as to leave the bit number of next code frame for so that rebuilds video image quality and declines；Instead
It, chooses too small initial parameter, not only makes image quality decrease, and can cause the waste of bandwidth resources；Do not influenceing to regard
Postpone a small amount of several frames in the case of feel and carry out near real-time communication, but the almost angle without correlation technique from real-time Transmission at present
Go to pay close attention to the selection of initial frame per second.
The content of the invention
It is an object of the invention to provide the parameter adaptive multidimensional bit rate control method based on video content features, with solution
Certainly above mentioned problem.
The update cycle of model parameter makes corresponding adjustment according to video Space-time Complexity, in extraction Space-time Complexity
When using sliding window as elementary cell；The parameter adaptive multidimensional code check of invention video content features proposed by the invention
Control method has higher accuracy, better than intra-class correlation method in the world, can effectively improve subjective quality and objective quality,
Particularly with the higher video sequence of Space-time Complexity；In addition, compared to intra-class correlation method in the world, the present invention also can somewhat subtract
Few computation complexity.
This method mainly includes the work of two parts：First, to ensure initial parameter for different video sequences all
Good performance can be shown；According to initial bandwidth and initial video content characteristic, the optimal initial code frame per second of dynamic calculation,
The initial frame rate value being calculated more conforms to the genuine property of sequence；Second, have for different video sequences different
Time and spatial coherence, identical video sequence difference section have different Space-time Complexities, based on video content dynamic more
The new multidimensional code check Controlling model parameter update cycle, go to obtain model parameter more using the complexity forecast model of spatial temporal adaptive
The new cycle；In this process, using sliding window as base unit, video content features is extracted, predict that next update cycle answers
Miscellaneous degree, with reference to the accuracy of current update cycle Rate Control, next update cycle length is obtained, and then determine next renewal week
The model parameter and quantization parameter and coding frame per second of phase.
The embodiments of the invention provide a kind of parameter adaptive multidimensional bit rate control method based on video content features, bag
Include following steps：
Step (1), input video sequence, obtain initial bandwidth, judge whether it is initial frame；
Step (2), if initial frame, according to the video content features of initial bandwidth and initial two frame calculate initial code
Frame per second, and then initial code quantization parameter is obtained according to initial frame per second；
Step (3), if non-initial frame, make to the coding video frames in the current update cycle, while with the update cycle
For unit, and associated video content information is extracted, calculate multidimensional code check Controlling model parameter；Unit is made with sliding window, when
Between domain and spatial domain extraction video content information, and combine current update cycle Rate Control accuracy, calculate it is next more
The length in new cycle；
Step (4), after multidimensional code check Controlling model parameter is got, optimized parameter, this hair are asked for according to model parameter
It is bright to go to calculate the frame per second f of next update cycle and initial quantization parameters q from correlation model.
In certain embodiments, it is preferably, in the step (2), specifically comprises the following steps：
Step (21), basis calculate preliminary initial frame per second to constant bit rate and video resolution；
Step (22), according to the video content information of front cross frame the preliminary initial frame per second got is adjusted, obtained
Take optimal initial frame per second；
Step (23), according to optimal initial frame per second, obtain initial quantization parameter.
In certain embodiments, it is preferably, in the step (22), specifically comprises the following steps：
Step (221), the first frame entropy of extraction are as initial airspace complexity；
Step (222), the first frame of extraction and the second frame frame difference are used as initial time domain complexity, while initial time domain is complicated
Degree and initial airspace complexity normalized；
Step (223), according to the first frame entropy and the first frame and the second frame frame difference the preliminary initial frame per second got is entered
Row adjustment.
In certain embodiments, it is preferably, in the step (3), specifically comprises the following steps：
Step (31), using the update cycle as elementary cell, extract the frame difference FD of consecutive frame, the MVM of motion-vector magnitude is put down
Average uMVM, motion-vector magnitude μMVMWith motion vector angle uMDARatio η (μMVM,uMDA), asked by forecast model P=HF
Modulus shape parameter, wherein P=[a, b, c, d, Rmax] it is each model parameter, for F to extract video content, H is prediction matrix,
Fixed value；
Step (32), using sliding window as elementary cell, obtain the complexity forecast model of spatial temporal adaptive, sliding window
It is made up of last continuous several frames of current update cycle, each update cycle terminates rear sliding window and moved backward, described sliding window
Intraoral video sequence is divided into for the ensemble space of two kinds of different scales according to time-domain and spatial domain；
Step (33), after the complexity forecast model of spatial temporal adaptive is got, ask for the length of next update cycle,
The length of next update cycle is adaptively adjusted according to code check precise control in the current update cycle simultaneously, to increase prediction
The adaptability of model.
In certain embodiments, it is preferably, in the step (32), specifically comprises the following steps：
Step (321), according to spatial domain, then the entropy of each frame is asked for the image sequence in input sliding window, including
The first frame of next update cycle, gets weighting entropy model；
Step (322), according to time-domain, then frame is asked for the image consecutive frame in the image sequence in input sliding window
Difference, get weighting frame it is poor, by the use of weighting frame difference as time domain complexity description, with the airspace complexity of weighted entropy model prediction
Description, by weighting frame difference and weighting entropy model obtain the complexity forecast model of spatial temporal adaptive.
In certain embodiments, it is preferably, in the step (4), according to the model parameter obtained by step (3), uses Q-R-
TQ models go to obtain the frame per second f of next update cycle and initial quantization parameters q.
Parameter adaptive multidimensional bit rate control method provided in an embodiment of the present invention based on video content features, it is and existing
Technology is compared, on the one hand, the acquisition of initial code frame per second uses empirical value in the prior art, and the present invention gives according to given
The Space-time Complexity of initial bit rate, video resolution and initial two frame obtains initial frame per second, and then obtains initial quantization parameter,
Ensure and ensure that initial parameter can show good performance for different video sequences.On the other hand, prior art
The model parameter update cycle takes fixed value or keeps constant in an encoding process, and the present invention is according to video content in cataloged procedure
The update cycle of middle dynamic renewal model parameter, from the current update cycle, video content is extracted by unit of sliding window
Feature, subsequent time update cycle length is gone out according to Space-time Complexity model prediction；Experiment shows, the video that this method is proposed
The parameter adaptive multidimensional bit rate control method of content characteristic can effectively improve subjective quality and objective quality, particularly with space-time
The higher video sequence of complexity, in addition, the present invention also can somewhat reduce the complexity of calculating.
Brief description of the drawings
Fig. 1 is the parameter adaptive multidimensional bit rate control method based on video content features in one embodiment of the invention
Frame diagram；
Fig. 2 is sliding window schematic diagram in one embodiment of the invention；
Fig. 3 is optimal frame per second and initial video content relation in one embodiment of the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
The present invention proposes a kind of parameter adaptive multidimensional bit rate control method based on video content features, method flow
As shown in figure 1, mainly include following four part.
Step 1, input video sequence, initial bandwidth is obtained, judge whether it is initial frame；
Step 2, if initial frame, extract the entropy of the first frame as initial airspace complexity, extract the first frame and the
The frame difference of two frames obtains initial frame per second, and then obtain initial quantization parameters according to initial frame per second as initial time domain complexity；
Step 3, if non-initial frame, ask for next update cycle length and it is next corrigendum modulus of periodicity shape parameter；
To the coding video frames in the current update cycle, and associated video content information is extracted, model is determined according to extraction video content
Parameter；The associated video content information extracted in sliding window, with reference to the accuracy of current update cycle Rate Control,
Determine the length of next update cycle；
Step 4, optimized parameter asked for according to model parameter.After model parameter is got, go to calculate from correlation model
Optimal frame per second and quantization parameter.
This method can effectively improve the subjective quality and objective quality of encoded video, and the video that is particularly suitable for use in changes violent
Sequence.It developed below and illustrates.
For step 1, first, initial bandwidth is obtained to the image sequence of input, in addition, within each update cycle
After coding video frames terminate, corresponding bandwidth need to be obtained again.
For step 2, optimal initial parameter divides two parts to complete, i.e., gets preliminary initial frame per second first, so
Final frame per second is obtained according to content characteristic afterwards；When calculating content complexity, the entropy for extracting the first frame is complicated as initial spatial domain
Degree, the difference of the first frame and the second frame is extracted as initial time domain complexity；Optimal initial frame per second is answered as initial bit rate and image
The function of miscellaneous degree
FRinitial=F (bpp)+G (Si1,1,Ti1,2) (1)
Wherein Si1,1Refer to the entropy of the first frame, Ti1,2Refer to that the frame of the first frame and the second frame is poor.The definition of entropy is：
NlRepresent the length of l-th of update cycle, EIl,kThe entropy of the k frames in the l update cycles is represented, such as following formula can be used
Son obtains：
Wherein, L is maximum grey level, and for 8 bit pixel precision, I value is 256.P (x) is grey level x's
Probability of occurrence；
The definition of frame difference：
Use Fl,kRepresent the gray value of the k frames in the l update cycles.Frame difference TIl,kIt is expressed as：
Wherein M and N represents the line number and columns of frame of video respectively；
Specifically comprise the following steps：
In coarse calculation stages：
Step (21)：According to given target bit rate, by formulaBpp value is calculated；
Step (22)：The bpp values obtained in step (1) are substituted into formula
Obtain F (bpp) value, wherein ε1={ a11,a12,a21,a22,a31,a32It is coefficient correlation, value -8.254,
13.88, -18.54,19.74, -51.66,26.99 } there is higher accuracy；
In the Exact calculation stage：
Step (23)：For application in real time, the entropy Si of the first frame of calculating1,1, while the first frame and the second frame is calculated
Frame difference Ti1,1；
The trim values of initial frame per second are further calculatedWherein m, n, h,
Z } it is coefficient correlation, value is that { -3, -5,75,3 } have higher accuracy；
Step (24)：The result of calculation of step (22) and step (23) is substituted into formula FRinitial=F (bpp)+G (Si1,1,
Ti1,2) in, obtain optimal FRinitialValue.
For step 3, specifically comprise the following steps：
Step (31) extracts the video content information of encoded frame using the update cycle as elementary cell, asks for model parameter；
The frame difference FD, (MVM) the average value u of motion-vector magnitude of consecutive frame are extracted within the update cycleMVM, motion vector
Amplitude μMVMWith motion vector angle (uMDA) ratio η (μMVM,uMDA), η (μMVM,uMDA)=μMVM/uMDA；
Model parameter, wherein P=[a, b, c, d, R are asked for by forecast model P=HFmax] it is each model parameter, F is to carry
Video content is taken out, H is prediction matrix, and value is
Step (32) is extracted Space-time Complexity, according to complexity forecast model, tied simultaneously using sliding window as base unit
The update cycle, Rate Control accuracy asked for the length of next update cycle before being fated；
It is next according to the acquisition of current update cycle Space-time Complexity forecast model and current update cycle Rate Control
The length of update cycle
Nl=Nl(Si,Ti,φ,Nmax,Nmin) (5)
Si refers to time domain complexity, and Ti refers to airspace complexity, and φ refers to the accuracy of Rate Control, NmaxIt is
The maximum length of update cycle, NminIt is the minimum update cycle.
A, the calculating of airspace complexity：
A kind of Complexity Measurement time is used as by the use of frame difference information；Sliding window is predicted substantially single as Space-time Complexity
Member, as shown in Figure 2.Sliding window refers to last continuous several frames of current update cycle；Each update cycle terminates rear sliding window
Move backward, it is as follows in sliding window frame difference gradient mean value calculation：
Wherein d represents the size of sliding window, and because sliding window is bigger, the degree of accuracy is higher, but time-consuming higher, consumption of trading off
When and the degree of accuracy, d values be 4.
WithFinal airspace complexity as prediction:
When sequence motion is very fast or frame is poor larger, now spatial coherence is higher, and corresponding value is smaller；Otherwise phase
Instead.
B, the calculating of time domain complexity；
It is as follows with the spatial information of weighted entropy model prediction, the equation：
WithFinal airspace complexity as prediction:
C, the length of next update cycle is adjusted with reference to update cycle Rate Control accuracy；
If the code check of actual consumption and larger difference to constant bit rate be present, show that scene changes are relatively violent, shorten
Update cycle adapts to the change of scene；
The length of next update cycle is adaptively adjusted according to code check precise control in the current update cycle, and increase is pre-
The adaptability of model is surveyed, the judgement of accuracy is as follows
Wherein OlIt is the code check of the predistribution of l-th of update cycle；BlIt is the code check of actual consumption in l update cycle；
Step A, B, C result are substituted into Nl=Nl(Si,Ti,φ,Nmax,Nmin), obtain
The present invention takes full advantage of time and spatial coherence, the normalizing of passage time forecast model and spatial prediction model
Change is handled, and the complexity forecast model of spatial temporal adaptive is obtained, according to complexity forecast model and current update cycle code check control
The accuracy of system obtains the length of next update cycle；In addition the complexity forecast model limit of spatial temporal adaptive proposed by the present invention
System is in sliding window, thus computation complexity is very small.
For step 4, specifically comprise the following steps：
Because Q-R-TQ has higher accuracy, after model parameter is got, the present invention goes to calculate from Q-R-TQ
Optimal frame per second and quantization parameter
Q-R-TQ code check models
Wherein RmaxIt is the actual bit rate when q takes minimum value, t to take maximum, a, b are model parameters, RmaxIt can measure
Come；
Q-R-TQ quality models
Wherein c, d are model parameter；
Optimized parameter (f*,q*) obtained with following manner
In the forecast model of spatial temporal adaptive of the present invention, operation, thus the meter of algorithm are mostly realized using plus and minus calculation
Calculation amount very little；Using the multidimensional code check Rate Control structures and methods of the present invention, for extensive dynamic network and multi-source heterogeneous
The application of network, there is provided very flexibly can improve subjective quality with good rate control techniques；And reduce calculating
Complexity.
The preferred embodiments of the present invention are these are only, are not intended to limit the invention, for those skilled in the art
For member, the present invention can have various modifications and variations.Any modification within the spirit and principles of the invention, being made,
Equivalent substitution, improvement etc., should be included in the scope of the protection.
Claims (5)
1. a kind of parameter adaptive multidimensional bit rate control method based on video content features, it is characterised in that including following step
Suddenly：
Step (1), input video sequence, obtain initial bandwidth, judge whether it is initial frame；
Step (2), if initial frame, calculate initial compile according to the Space-time Complexity information characteristics of initial bandwidth and initial two frame
Code frame per second, and then initial code quantization parameter is obtained according to initial frame per second；
Step (3), if non-initial frame, to the coding video frames in the current update cycle, while be used as using the update cycle single
Member, and the frame for extracting consecutive frame is poor, the ratio of the average value of motion-vector magnitude, motion-vector magnitude and angle, computation model
Parameter, calculate multidimensional code check Controlling model parameter；Unit is made with sliding window, in time-domain and spatial domain extraction Space-time Complexity
Information, according to Space-time Complexity forecast model, and the accuracy of current update cycle Rate Control is combined, calculate next renewal week
The length of phase；
Step (4), after multidimensional code check Controlling model parameter is got, optimized parameter is asked for according to model parameter, from Q-R-
TQ models go to calculate the frame per second f of next update cycle and initial quantization parameters q.
2. the parameter adaptive multidimensional bit rate control method based on video content features described in claim 1, it is characterised in that
In the step (2), specifically comprise the following steps：
Step (21), basis calculate preliminary initial frame per second to constant bit rate and video resolution；
Step (22), according to the video content information of front cross frame the preliminary initial frame per second got is adjusted, obtained most
Excellent initial frame per second；
Step (23), according to optimal initial frame per second, obtain initial quantization parameter.
3. the parameter adaptive multidimensional bit rate control method based on video content features described in claim 2, it is characterised in that
In the step (22), specifically comprise the following steps：
Step (221), the first frame entropy of extraction are as initial airspace complexity；
Step (222), the first frame of extraction and the second frame frame difference be used as initial time domain complexity, at the same by initial time domain complexity with
Initial airspace complexity normalized；
Step (223), according to the first frame entropy and the first frame and the second frame frame difference the preliminary initial frame per second got is adjusted
It is whole.
4. the parameter adaptive multidimensional bit rate control method based on video content features described in claim 1, it is characterised in that
In the step (3), specifically comprise the following steps：
Step (31), using the update cycle as elementary cell, extract the frame difference FD of consecutive frame, the MVM average values of motion-vector magnitude
uMVM, motion-vector magnitude μMVMWith motion vector angle uMDARatio η (μMVM,uMDA), mould is asked for by forecast model P=HF
Shape parameter, wherein P=[a, b, c, d, Rmax] it is each model parameter, for F to extract video content, H is prediction matrix, fixed
Value；
Step (32), using sliding window as elementary cell, obtain the complexity forecast model of spatial temporal adaptive, sliding window is by working as
Last continuous a few frame compositions of preceding update cycle, each update cycle terminates rear sliding window and moved backward, in described sliding window
Video sequence is divided into for the ensemble space of two kinds of different scales according to time-domain and spatial domain；
Step (33), after the complexity forecast model of spatial temporal adaptive is got, ask for the length of next update cycle, simultaneously
The length of next update cycle is adaptively adjusted according to code check precise control in the current update cycle, to increase forecast model
Adaptability.
5. the parameter adaptive multidimensional bit rate control method based on video content features described in claim 4, it is characterised in that
In the step (32), specifically comprise the following steps：
Step (321), according to spatial domain, then the entropy of each frame is asked for the image sequence in input sliding window, including next
The first frame of update cycle, gets weighting entropy model；
Step (322), according to time-domain, then it is poor to ask for frame to the image consecutive frame in the image sequence in input sliding window,
Get that weighting frame is poor, by the use of weighting frame difference as the description of time domain complexity, with the airspace complexity of weighted entropy model prediction
Description, the complexity forecast model of spatial temporal adaptive is obtained by weighting frame difference and weighting entropy model.
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| CN101094411A (en) * | 2007-07-03 | 2007-12-26 | 芯瀚电子技术（上海）有限公司 | Code rate control method of video code |
| WO2010005691A1 (en) * | 2008-06-16 | 2010-01-14 | Dolby Laboratories Licensing Corporation | Rate control model adaptation based on slice dependencies for video coding |
| CN101854524A (en) * | 2009-03-31 | 2010-10-06 | 郑州大学 | Method for controlling code rate of video encoder with very low bit rate |
| CN103179394A (en) * | 2013-01-21 | 2013-06-26 | 北京航空航天大学 | I frame rate control method based on stable area video quality |
| CN103517069A (en) * | 2013-09-25 | 2014-01-15 | 北京航空航天大学 | HEVC intra-frame prediction quick mode selection method based on texture analysis |
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| CN109889816A (en) * | 2019-02-19 | 2019-06-14 | 西安电子科技大学 | A kind of video quality evaluation method based on spatial and temporal resolution, device, equipment and storage medium |
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