CN105763882B - For error concealing method and its system in the frame of decoding end - Google Patents
For error concealing method and its system in the frame of decoding end Download PDFInfo
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Abstract
The present invention relates to error concealing method and its systems in a kind of frame for decoding end, wherein, for error concealing method in the frame of decoding end, comprising the following steps: carry out edge detection to the loss macro block of present frame in video sequence, obtain the edge strength of the loss macro block；According to the size of edge strength, the state model of the loss macro block is determined；State model is smooth mode, direction mode or texture pattern；According to the incidence of the state model of the loss macro block of video frame in video sequence within a preset period of time, the determination state model of the loss macro block is obtained；According to state model is determined, error concealing is carried out to the loss macro block by corresponding restoration methods；Restoration methods are weighted interpolation method, directional interpolation method or adjacent block penalty method.The present invention can greatly improve the accuracy of error concealing in frame, while can preferably promote the Quality of recovery of video image.
Description
Technical field
The present invention relates to video compression coding fields, more particularly to error concealing method in a kind of frame for decoding end
And its system.
Background technique
Main problem in transmission of video is damage of the channel to compressed video data, and the unreliability of communication channel will lead to
The video frequency data quality of transmission declines, therefore is very important in decoding end progress error concealing.Error concealing is decoding end
The effective technology of error of transmission is repaired using correlation of the video data on spatially and temporally, Error concealment techniques itself are simultaneously
It cannot restore its initial data, just with the image correlation over time and space of video, search out other phase
The data of pass come replace error or loss data, try improve application terminal video effect.It is logical for time and space
Often pass through different types of error concealment mode: error concealing and interframe error concealing in frame.Error concealing, that is, airspace is wrong in frame
(spatial error concealment, SEC) accidentally is hidden, is carried out using the information for being properly received macro block around erroneous macroblock
Weighted calculation is to obtain the recovery data of erroneous macroblock.For error concealing in frame, traditional technology is mainly using flat including weighting
The methods of equal interpolation method, directional interpolation method and most possible prediction mode look-up table.
In the different frame of application when error concealing method, the loss of the judgment method of traditional technology aiming at present frame
Macro block carries out edge detection, carries out different error concealings according to the extrorse intensity in side.But during realization, invention
People has found that at least there are the following problems in traditional technology: the accuracy that above-mentioned judgment method carries out error concealing in frame is lower.
Summary of the invention
Based on this, it is necessary to for the problem of the stage division accuracy deficiency of error concealing in traditional technology frame, provide
Error concealing method and its system in a kind of frame for decoding end.
To achieve the goals above, the embodiment of technical solution of the present invention are as follows:
On the one hand, error concealing method in a kind of frame for decoding end is provided, comprising the following steps:
Edge detection is carried out to the loss macro block of present frame in video sequence, obtains the edge strength of the loss macro block；
According to the size of edge strength and the direction variance of edge strength, the state model of the loss macro block is determined；Shape
Morphotype formula is smooth mode, direction mode or texture pattern；
According to the incidence of the state model of the loss macro block of video frame in video sequence within a preset period of time, obtain
The determination state model of the loss macro block；
According to state model is determined, error concealing is carried out to the loss macro block by corresponding restoration methods；Restoration methods
For weighted interpolation method, directional interpolation method or adjacent block penalty method.
On the other hand, error concealing system in a kind of frame is provided, comprising:
Edge detection module carries out edge detection for the loss macro block to present frame in video sequence, obtains the loss
The edge strength of macro block；
First mode determining module, for according to the size of edge strength and the direction variance of edge strength, determining should
Lose the state model of macro block；State model is smooth mode, direction mode or texture pattern；
Second mode determining module, for according to the loss macro block of video frame in video sequence within a preset period of time
The incidence of state model obtains the determination state model of the loss macro block；
Data recovery module, for being carried out to the loss macro block by corresponding restoration methods according to state model is determined
Error concealing；Restoration methods are weighted interpolation method, directional interpolation method or adjacent block penalty method.
Above-mentioned technical proposal has the following beneficial effects:
The present invention is for error concealing method and its system in the frame of decoding end, adoption status schema hierarchy method and corresponding
Restoration methods can be greatly improved in frame compared to demosaicing method simple in conventional video encoding and decoding reference model
The accuracy of error concealing；The calculation about state incidence accordingly is added while according to edge strength and direction classification
Method is lost the accuracy of the state model classification of macro block by improving using state model as Studying factors, is adopted on this basis
With corresponding restoration methods, the Quality of recovery of video image can be preferably promoted.
Detailed description of the invention
Fig. 1 is flow diagram of the present invention for error concealing method embodiment 1 in the frame of decoding end；
Fig. 2 is realization of the present invention for weighted mean approach in one specific embodiment of error concealing method in the frame of decoding end
Schematic diagram；
Fig. 3 is realization of the present invention for directional interpolation method in one specific embodiment of error concealing method in the frame of decoding end
Schematic diagram；
Fig. 4 is flow diagram of the present invention for one specific embodiment of error concealing method in the frame of decoding end；
Fig. 5 is simulation result schematic diagram of the present invention for one specific embodiment of error concealing method in the frame of decoding end；
Fig. 6 is structural schematic diagram of the present invention for error concealing system embodiment 1 in the frame of decoding end.
Specific embodiment
To facilitate the understanding of the present invention, a more comprehensive description of the invention is given in the following sections with reference to the relevant attached drawings.In attached drawing
Give preferred embodiment of the invention.But the invention can be realized in many different forms, however it is not limited to this paper institute
The embodiment of description.On the contrary, purpose of providing these embodiments is make it is more thorough and comprehensive to the disclosure.
Unless otherwise defined, all technical and scientific terms used herein and belong to technical field of the invention
The normally understood meaning of technical staff is identical.Term as used herein in the specification of the present invention is intended merely to description tool
The purpose of the embodiment of body, it is not intended that in the limitation present invention.Term " and or " used herein includes one or more phases
Any and all combinations of the listed item of pass.
The present invention is for error concealing method embodiment 1 in the frame of decoding end:
Stage division accuracy in order to solve the problems, such as error concealing in traditional technology frame is insufficient, and the present invention provides one
Kind is for error concealing method embodiment 1 in the frame of decoding end；Fig. 1 is the present invention for error concealing method in the frame of decoding end
The flow diagram of embodiment 1；As shown in Figure 1, may comprise steps of:
Step S110: edge detection is carried out to the loss macro block of present frame in video sequence, obtains the side of the loss macro block
Edge intensity；
Step S120: according to the size of edge strength and the direction variance of edge strength, the shape of the loss macro block is determined
Morphotype formula；State model is smooth mode, direction mode or texture pattern；
Step S130: according to the hair of the state model of the loss macro block of video frame in video sequence within a preset period of time
Raw rate, obtains the determination state model of the loss macro block；
Step S140: according to state model is determined, error concealing is carried out to the loss macro block by corresponding restoration methods；
Restoration methods are weighted interpolation method, directional interpolation method or adjacent block penalty method.
In one embodiment, step S120 is according to the size of edge strength and the direction variance of edge strength, really
Surely the step of state model of loss macro block may include:
When edge strength is less than default edge strength threshold value, determine that the state model for losing macro block is smooth mode；
When edge strength is greater than default edge strength threshold value, the direction variance of edge strength is obtained；
When direction variance is less than preset direction variance threshold values, determine that the state model for losing macro block is direction mode；
When direction variance is greater than preset direction variance threshold values, determine that the state model for losing macro block is texture pattern.
Specifically, t can be definedthThe kth of framethA N × N block isDefine video sequence t frame (tthFrame)
K-th of N × N block (kthBlock) beIt first can be based on the marginal information handle for losing macro blockIt is divided into three kinds of different conditionsSmooth mode (SP), direction mode (DP) and texture pattern (TP) can be calculated with a kind of simple and common sobel
Son carries out edge detection, when the edge strength G for losing macro block is less than some threshold value (default edge strength threshold value T1) when draw
For smooth mode, (edge strength threshold value T is preset when being greater than some threshold value1) when, then calculate the variance of edge strength GVariance
Less than some threshold value (preset direction variance threshold values T2) when be direction mode, otherwise be texture pattern.This classification mode can
To be indicated based on following formula:
Wherein,Indicate that the state model of loss macro block, SP indicate smooth mode, DP indicates that direction mode, TP indicate line
Reason mode, G indicate edge strength, T1Indicate default edge strength threshold value, T2Indicate preset direction variance threshold values,Indicate edge
The direction variance of intensity.In one embodiment, for presetting edge strength threshold value T1With preset direction variance threshold values T2, can
With the edge pixel by the different types of video image blocks of statistics come respectively to T1And T2Default suitable value.
The embodiment of the present invention proposes a kind of texture pattern to handle some textural characteristics image abundant, but not only considers
The marginal information of current frame loss macro block, can be using three kinds of state models as study based on Hedge algorithm proposed by the present invention
The factor can obtain the determination state model for losing macro block by step S130, can specifically include in one embodiment
Following steps:
Using the state model for losing macro block generation within a preset period of time as Studying factors, expression is obtained in predetermined time
Vector does not occur for the loss macro block of the not degree of generation of state model；
Summation operation is carried out to vector does not occur, obtains the loss for indicating the incidence of state model within a preset period of time
The accumulation vector of macro block；
Matrix operation is carried out according to accumulation vector, obtains a possibility that state model occurs weight；
Possibility weight is normalized, a possibility that losing macro block vector is obtained, according to possibility vector
Size obtains the determination state model for losing macro block.
Specifically, when being defined on predetermined time tThe vector that do not occur be For indicating t moment state mould
Formula does not occur.Accumulation vector is defined simultaneouslyTo indicate each state model in the frequency of time window [t-T, t].When one
State can specify its vector element when occurring be 0.SoWithIt is represented by as follows:
Wherein,Vector does not occur for expression, and T indicates the size of time window,Indicate that state model, SP indicate smooth mould
Formula, DP indicate that direction mode, TP indicate texture pattern；
Based on following formula, according to the accumulation vector that vector acquisition loss macro block does not occur, accumulation vector indicates state mould
Formula time window [t-T, t] occurrence frequency,
Wherein,Vector does not occur for expression,Indicate accumulation vector,Indicate the not degree of generation of smooth mode in t
The accumulation at quarter,Indicate accumulation of the not degree of generation in t moment of direction mode,Indicate the not degree of generation of texture pattern in t
The accumulation at moment；
In Hedge algorithm, a possibility that state model, increases with corresponding incidence, according to accumulation vector, base
In following formula obtain lose macro block state model occur a possibility that weight,
Wherein,Indicate possibility weight,Indicate smooth mode a possibility that weight,Indicate direction mode
A possibility that weight,Indicate texture pattern a possibility that weight,Indicate the initial weight of smooth mode,Table
Show the initial weight of direction mode,Indicate that the initial weight of texture pattern, η indicate adjustable study index x constant；
Possibility weight is normalized, a possibility that losing macro block vector is obtained based on following formula,
Wherein,Indicate a possibility that losing macro block vector,Indicate smooth mode a possibility that vector,It indicates
A possibility that direction mode vector,Indicate texture pattern a possibility that vector；
According to possibility vector, the determination state model for losing macro block is obtained based on following formula,
Wherein,It indicates to determine state model.The state model for losing macro block can be determined by above-mentioned algorithm, then
It can carry out losing the recovery of macro block using corresponding error concealing method.
It is hidden to help to improve mistake in frame by the classification to macro block progress texture phase information is lost for the embodiment of the present invention
The accuracy of hiding, and different texture status information is needed to use corresponding suitable hidden method, further to promote video figure
The Quality of recovery of picture, in one embodiment, step S140 is according to state model is determined, by corresponding restoration methods to losing
Losing the step of macro block carries out error concealing may include:
It is hidden to macro block progress mistake is lost by weighted interpolation method when determining above-mentioned determining state model is smooth mode
Hiding；Specifically, weighted interpolation method is to realize the pixel interpolating in space using correct macro block adjacent around it, for impaired
Each of macro block pixel will be used and be weighted interpolation with four boundary pixel points of a line or same row with it,
A kind of restoration methods proper for the recovery of image flat site and more common.
It is hidden to macro block progress mistake is lost by directional interpolation method when determining above-mentioned determining state model is direction mode
Hiding；Specifically, after carrying out edge detection using sobel operator, each direction can be calculated using directional interpolation method
The pixel number in integrated intensity or accumulation gradient direction obtains the maximum direction of gradient, then carries out along these lines slotting
Value, can smoothly lose the information of macro block to greatest extent.
When determining above-mentioned determining state model is texture pattern, mistake is carried out to macro block is lost by adjacent block penalty method
It hides.Specifically, texture pattern defined in the embodiment of the present invention can be the image as meadow, and use adjacent block
Compensation method is not influencing picture quality with the pixel of the pixel direct compensation lost blocks of the block of adjacent top or the left side
Under the premise of can greatly reduce algorithm complexity.
In one embodiment, step S110 carries out edge detection to the loss macro block of present frame, obtains losing macro block
Edge strength the step of may include:
Edge detection is carried out by loss macro block of the Sobel operator to present frame, obtains edge strength.
The present invention for decoding end frame in error concealing method embodiment 1, by using state model stage division with
Corresponding restoration methods can be greatly improved compared to demosaicing method simple in conventional video encoding and decoding reference model
The accuracy of error concealing in frame；It is added while according to edge strength and direction classification accordingly about state incidence
Algorithm loses the accuracy of the state model classification of macro block by improving using state model as Studying factors, on this basis
Using corresponding restoration methods, the Quality of recovery of video image can be preferably promoted.
It is special on a personal computer by modifying H.264 in order to illustrate technical solution of the present invention in more detail
For official reference software JM (joint model), wherein JM86 is the most common experiment version of JM, and the present invention one is embodied
Example can be achieved by following below scheme:
Based on the hierarchy model of Hedge algorithm, when allowing to carry out error concealing in frame, carry out side that can be more accurate
The detection of edge pixel is simultaneously divided into three kinds of different state models, while taking three kinds of different hidden methods, improves picture quality.
Three kinds of different state models that the embodiment of the present invention proposes are respectively smooth mode, direction mode and texture mould
Formula.When edge strength is less than threshold value T1When, illustrate that its marginal information is not obvious, it can be classified as smooth mode.Work as side
Edge intensity is greater than threshold value T1When, if edge pixel direction is distributed (i.e. in spike), strongest side can be calculated
Edge direction can be classified as direction mode this.And if edge pixel directional spreding is more balanced (i.e.), it can be with
It is classified as texture pattern.
For the default edge strength threshold value T in state model division1With preset direction variance threshold values T2, system can be passed through
The edge pixel of different types of video image blocks is counted to find a proper line of demarcation.
By using these three state models as Studying factors, using the model based on Hedge algorithm, so that it may with accumulation
Method more accurately determine which kind of state model lost blocks belong to, next for three kinds of differences of use of three kinds of different modes
Hidden method: for smooth mode, using weighted interpolation method, (Fig. 2 is the present invention for error concealing in the frame of decoding end
The realization schematic diagram of weighted mean approach in one specific embodiment of method)；For direction mode, use directional interpolation method (Fig. 3 for
Realization schematic diagram of the present invention for directional interpolation method in one specific embodiment of error concealing method in the frame of decoding end)；For
Texture pattern, using adjacent block compensation method.
It can then proceed in Fig. 4 modification JM reference software, Fig. 4 is the present invention for error concealing method in the frame of decoding end
The flow diagram of one specific embodiment；As shown in figure 4, Hedge algorithm hierarchy model is added in error concealing function in frame
Function is carrying out different restoration methods, is natively using weighted interpolation in JM86 then for different state models
Method, so needing separately to write code (this portion of techniques energy of directional interpolation and adjacent block compensation in embodiments of the present invention
It is enough realized using traditional technology, does not repeat to discuss herein).
The algorithm write is tested by choosing different sequences, is carried out while then comparing Y-PSNR (PSNR)
The evaluation and test of subjective quality, the algorithm that the test result based below table can be seen that the embodiment of the present invention proposes obviously have more
Good Quality of recovery, the resulting PSNR value of algorithm is respectively 30.10dB and 28.51dB through the embodiment of the present invention, more traditional skill
The canonical algorithm of art distinguishes height 4.86dB and 3.06dB；Test result is as shown in table 1:
The comparison of the PSNR simulation result of 1 algorithm of the embodiment of the present invention of table and canonical algorithm
Above-mentioned state model stage division is simple compared in coding and decoding video reference model with corresponding restoration methods
Demosaicing, it is more scientific and accurate, intensity not only according to edge pixel point and direction classification and joined Hedge calculation
Method, which carries out study, makes classification relatively reliable, therefore the Quality of recovery of video image also can be promoted preferably, as shown in figure 5,
Fig. 5 is simulation result schematic diagram of the present invention for one specific embodiment of error concealing method in the frame of decoding end, wherein 510
For original image；520 be the canonical algorithm in traditional technology；530 is using the processing results of algorithm in the embodiment of the present invention；Such as
The precision that traditional technology shown in 520 restores is not high, can generate many false edges (such as the background parts on personage's head portrait left side),
Seriously affect visual effect；As indicated at 530, the visual effect for the image that algorithm obtains through the embodiment of the present invention will be substantially better than
Traditional technology.
The present invention is for error concealing system embodiment 1 in the frame of decoding end:
Based on the technical idea of error concealing method in the above-mentioned frame for decoding end, while in order to solve traditional technology frame
The problem of the stage division accuracy deficiency of interior error concealing, the present invention also provides mistake in a kind of frame for decoding end is hidden
Hide system embodiment 1；Fig. 6 is structural schematic diagram of the present invention for error concealing system embodiment 1 in the frame of decoding end, is such as schemed
Shown in 6, may include:
Edge detection module 610 carries out edge detection for the loss macro block to present frame in video sequence, obtains this and lose
Lose the edge strength of macro block；
First mode determining module 620, for determining according to the size of edge strength and the direction variance of edge strength
The state model of the loss macro block；State model is smooth mode, direction mode or texture pattern；
Second mode determining module 630, it is macro for the loss according to video frame in video sequence within a preset period of time
The incidence of the state model of block obtains the determination state model of the loss macro block；
Data recovery module 640, for according to determine state model, by corresponding restoration methods to the loss macro block into
Row error concealing；Restoration methods are weighted interpolation method, directional interpolation method or adjacent block penalty method.
In a specific embodiment, first mode determining module 620 may include:
Smooth mode determining module 622, for determining and losing macro block when edge strength is less than default edge strength threshold value
State model be smooth mode；
Variance module 624 is calculated, for obtaining the side of edge strength when edge strength is greater than default edge strength threshold value
To variance；
Direction mode determining module 626, for determining and losing macro block when direction variance is less than preset direction variance threshold values
State model be direction mode；
Texture pattern determining module 628, for determining and losing macro block when direction variance is greater than preset direction variance threshold values
State model be texture pattern.
Second mode determining module 630 may include:
Vector determining module 632 does not occur, for using within a preset period of time lose macro block occur state model as
Studying factors, obtaining indicates that vector does not occur for the loss macro block of the not degree of generation in predetermined time state model；
Vector determining module 634 is accumulated, for vector progress summation operation does not occur, obtaining to indicate state model pre-
If the accumulation vector of the loss macro block of the incidence in the period；
Possibility weight determination module 636 obtains what state model occurred for carrying out matrix operation according to accumulation vector
Possibility weight；
Possibility vector determining module 638, for possibility weight to be normalized, obtain lose macro block can
Energy property vector obtains the determination state model for losing macro block according to the size of possibility vector.
Data recovery module 640 may include:
Smooth mode recovery module 642, for being inserted by weighting when determining above-mentioned determining state model is smooth mode
Value method carries out error concealing to macro block is lost；
Direction mode recovery module 644, for being inserted by direction when determining above-mentioned determining state model is direction mode
Value method carries out error concealing to macro block is lost；
Texture pattern recovery module 646, for passing through adjacent block when determining above-mentioned determining state model is texture pattern
Penalty method carries out error concealing to macro block is lost.
Edge detection module 610 can be used for carrying out edge detection by loss macro block of the Sobel operator to present frame, obtain
To edge strength.
The present invention is for error concealing system embodiment 1 in the frame of decoding end, adoption status schema hierarchy method and corresponding
Restoration methods can be greatly improved in frame compared to demosaicing method simple in conventional video encoding and decoding reference model
The accuracy of error concealing；The calculation about state incidence accordingly is added while according to edge strength and direction classification
Method is lost the accuracy of the state model classification of macro block by improving using state model as Studying factors, is adopted on this basis
With corresponding restoration methods, the Quality of recovery of video image can be preferably promoted.
Each technical characteristic of embodiment described above can be combined arbitrarily, for simplicity of description, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, all should be considered as described in this specification.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to protection of the invention
Range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (8)
1. error concealing method in a kind of frame for decoding end, which comprises the following steps:
Edge detection is carried out to the loss macro block of present frame in video sequence, obtains the edge strength for losing macro block；
According to the size of the edge strength and the direction variance of the edge strength, the state mould for losing macro block is determined
Formula；The state model for losing macro block is smooth mode, direction mode or texture pattern；
According to the incidence of the state model of the loss macro block of video frame in the video sequence within a preset period of time, obtain
Take the determination state model for losing macro block；
According to the determining state model, error concealing is carried out to the loss macro block by corresponding restoration methods；It is described extensive
Compound method is weighted interpolation method, directional interpolation method or adjacent block penalty method；
Wherein, the preset time period is time window [t-T, t]；In the time window [t-T, t] in the video sequence
The incidence of the state model of the loss macro block of video frame is accumulation vectorThe accumulation vectorIndicate each shape
Frequency of the morphotype formula in time window [t-T, t]；
Wherein, according to the size of the edge strength and the direction variance of the edge strength, the loss macro block is determined
The step of state model includes:
When the edge strength is less than default edge strength threshold value, determine that the state model for losing macro block is smooth mould
Formula；
When the edge strength is greater than the default edge strength threshold value, the direction variance of the edge strength is obtained；
When the direction variance is less than preset direction variance threshold values, determine that the state model for losing macro block is direction mould
Formula；
When the direction variance is greater than the preset direction variance threshold values, determine that the state model for losing macro block is texture
Mode.
2. error concealing method in the frame according to claim 1 for decoding end, which is characterized in that according to when default
Between in section in the video sequence state model of the loss macro block of video frame incidence, obtain the macro block of losing
The step of determining state model include:
Using the state model for losing macro block generation within a preset period of time, as Studying factors, obtaining is indicated in predetermined time
Vector does not occur for the loss macro block of the not degree of generation of the state model；
Summation operation is carried out to the vector that do not occur, obtaining indicates the incidence of the state model within a preset period of time
The accumulation vector for losing macro block；
Matrix operation is carried out according to the accumulation vector, obtains a possibility that state model occurs weight；
A possibility that possibility weight is normalized, the loss macro block is obtained vector, according to the possibility
Property vector size, obtain it is described lose macro block determination state model.
3. error concealing method in the frame according to claim 1 for decoding end, which is characterized in that according to the determination
State model, by corresponding restoration methods to the loss macro block carry out error concealing the step of include:
When determining the determining state model is smooth mode, the loss macro block is carried out by the weighted interpolation method wrong
Accidentally hide；
When determining the determining state model is direction mode, the loss macro block is carried out by the directional interpolation method wrong
Accidentally hide；
When determining the determining state model is texture pattern, the loss macro block is carried out by the adjacent block penalty method
Error concealing.
4. error concealing method in the frame according to claim 1 for decoding end, which is characterized in that lost to present frame
Losing the step of macro block carries out edge detection, obtains the edge strength for losing macro block includes:
Edge detection is carried out by loss macro block of the Sobel operator to present frame, obtains the edge strength.
5. error concealing system in a kind of frame for decoding end characterized by comprising
Edge detection module carries out edge detection for the loss macro block to present frame in video sequence, and it is macro to obtain the loss
The edge strength of block；
First mode determining module, for according to the size of the edge strength and the direction variance of the edge strength, really
The fixed state model for losing macro block；The state model for losing macro block is smooth mode, direction mode or texture pattern；
Second mode determining module, for the loss macro block according to video frame in the video sequence within a preset period of time
State model incidence, obtain it is described lose macro block determination state model；
Data recovery module, for according to the determining state model, by corresponding restoration methods to the loss macro block into
Row error concealing；The restoration methods are weighted interpolation method, directional interpolation method or adjacent block penalty method；
Wherein, the preset time period is time window [t-T, t]；In the time window [t-T, t] in the video sequence
The incidence of the state model of the loss macro block of video frame is accumulation vectorThe accumulation vectorIndicate each state
Frequency of the mode in time window [t-T, t]；
Wherein, the first mode determining module includes:
Smooth mode determining module, for when the edge strength is less than default edge strength threshold value, determining that the loss is macro
The state model of block is smooth mode；
Variance module is calculated, for it is strong to obtain the edge when the edge strength is greater than the default edge strength threshold value
The direction variance of degree；
Direction mode determining module, for when the direction variance is less than preset direction variance threshold values, determining that the loss is macro
The state model of block is direction mode；
Texture pattern determining module, for being lost described in determination when the direction variance is greater than the preset direction variance threshold values
The state model for losing macro block is texture pattern.
6. error concealing system in the frame according to claim 5 for decoding end, which is characterized in that the second mode
Determining module includes:
Vector determining module does not occur, for using the state model for losing macro block generation within a preset period of time as study
The factor, obtain the loss macro block for indicating the not degree of generation of the state model described in predetermined time does not occur vector；
Vector determining module is accumulated, for carrying out summation operation to the vector that do not occur, obtaining indicates that the state model exists
The accumulation vector of the loss macro block of incidence in preset time period；
Possibility weight determination module obtains the state model and occurs for carrying out matrix operation according to the accumulation vector
A possibility that weight；
Possibility vector determining module obtains the loss macro block for the possibility weight to be normalized
Possibility vector obtains the determination state model for losing macro block according to the size of the possibility vector.
7. error concealing system in the frame according to claim 5 for decoding end, which is characterized in that the data are restored
Module includes:
Smooth mode recovery module, for passing through the weighted interpolation when determining the determining state model is smooth mode
Method carries out error concealing to the loss macro block；
Direction mode recovery module, for passing through the directional interpolation when determining the determining state model is direction mode
Method carries out error concealing to the loss macro block；
Texture pattern recovery module, for being mended by the adjacent block when determining the determining state model is texture pattern
It repays method and error concealing is carried out to the loss macro block.
8. error concealing system in the frame according to claim 5 for decoding end, which is characterized in that
The edge detection module is used to carry out edge detection by loss macro block of the Sobel operator to present frame, obtains described
Edge strength.
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