CN101867812B - Method for estimating and predicting video data compression motion by using edge effect to predict video data compression motion - Google Patents
Method for estimating and predicting video data compression motion by using edge effect to predict video data compression motion Download PDFInfo
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Abstract
The invention relates to a method for estimating and predicting video data compression motion by using the edge effect, belonging to the field of the data compression. The method for partitioning the round macroblock which is provided with an intersection part is adopted; the intermediate value is obtained according to the intersection part motion vector to determine the macroblock motion vector prediction value; the initial searching and the initial matching module determination are carried out, and the secondary search range is determined and the video data compression motion is estimated by taking the matching module which is initially determined as the base point. The method can improve the accuracy and the speed of estimating the video data compression motion and can effectively eliminate the square block in the video.
Description
Technical field:
The present invention relates to field of video compression, particularly towards the mobile media video data compression method for estimating of digital home.
Background technology
In multimedia application, the shared data volume of one 640 * 480 256 color images is 300kB, and dynamic video requires per second to play 25～30 two field pictures; Thereby play 256 color look video images with 640 * 480 window; Even do not having under the situation of voice data, also require per second to handle the data volume about 8MB, so in order to pass through under finite element network bandwidth and the speed; Realize multimedia smooth playing, be necessary dynamic video is carried out maximum processed compressed.
Multimedia data volume and amount of information relation are I=D-du, and wherein, I is an amount of information, and D is a data volume, and du is an amount of redundancy.Amount of information is the key data that will transmit, and data redundancy is useless data, there is no need transmission.Have mass of redundancy data on the vision signal, this is the basis of carrying out video data compression, and the redundancy of multimedia video signal is present in structure and statistics two aspects.In structure aspects; Redundancy shows as very strong spatial coherence and temporal correlation, and spatial coherence is an in-frame correlation, and temporal correlation is a frame-to-frame correlation; Because the variation of the most of regional signal of the image of consecutive frame is slow; Especially background parts is almost constant, thus vision signal between phase portion pixel, there is stronger correlation in the ranks and even between consecutive frame in phase portion, this correlation just shows as spatial redundancy and time redundancy.Aspect statistics; Redundancy shows as the limitation of human eye when observing image; Human eye all has one to delimit to image detail resolution, Motion Resolution rate and contrast resolution's sensation; So considerable image information is inessential for human eye, these spatial redundancies and time redundancy have also been brought wide space for video compression.
At present, mainly utilize three kinds of means that image is compressed: to utilize discrete cosine transform (DCT) and vector quantization to eliminate in-frame correlation, utilize estimation to eliminate frame-to-frame correlation, the redundancy of utilizing the digital coding of entropy coding removal of images to bring.The method of traditional elimination frame-to-frame correlation is an estimation; Promptly,, calculate the motion vector of the data of present frame with respect to the former frame data at first in former frame search and its zone of mating most for the data of current image frame; After searching out the result, both differences are encoded.Multiple motion estimation algorithm is arranged at present; Wherein modal method is a BMA; Be the sub-piece that every two field picture is divided into the N*N pixel of two dimension, General N is 16, supposes that all pixels in every sub-block are done equal translational motion; The N*N piece of the present frame piece that search is mated with it most in portion's territory window of the corresponding sub-piece of former frame, the displacement of the match block of current sub-block and preceding frame on two dimensional surface is the motion vector that estimation obtains.In the BMA method of the sub-piece of search matched also have multiple, like full search method, three step search methods (3SS), intersection search methods, new three step search methods (3NSS), diamond search, hexagon motion search, melee shape motion search.Wherein full search method is each macro block for present frame; In the particular range (being generally the portion territory) of preceding frame, calculate the piece matching value of each point; Each point in this territory is match point; Then that the smallest match value is corresponding match point is as optimal match point, and the motion vector that optimal match point is corresponding is the motion vector of current macro.
At present the common piece division methods of BMA is for being the sub-piece of N*N pixel with image division, and General N is 16.Be mutual independence between each macro block, do not have the part that intersects.When doing the motion vector predictor of current macro, generally be the motion vector choosing left macro block, just going up macro block, right macro block as a reference.In fact; The prediction of macro block can reflect its variation should and piece and piece between the change direction and the motion vector of pixel value of intersection; And at present common piece division methods lacks this emphasis to being ignored; Also cause to a great extent in the time of video playback, under the low situation of resolution, can give people's's a kind of " grid " effect unavoidably.At present; Another emphasis of video data compression estimation is the speed problem of the search of matched sub-block; The new three step search methods (3NSS), diamond search, hexagon motion search, the melee shape method for searching motion that successively occur have improved the speed of search to a certain extent; And then improved the compression efficiency of video, and media delivery and broadcast but the high definition that is intended for network application flows, this compression efficiency still is difficult to satisfy the practical application needs.
Summary of the invention
The present invention seeks to disclose a kind of different macroblock partitions method that is different from present video compression motion estimation, and utilize that intersection can reflect the variation between piece and the piece more really to the motion-vector prediction that carries out of current macro between each macro block; In addition, the present invention is also through improving the search rate of matched sub-block with two step search methods, and then the compression speed and the decrement that improve video are to satisfy the requirement of digital home videos netcast.
The object of the invention is realized through following technical scheme:
A kind of video data compression method for estimating that utilizes edge effect to carry out motion prediction is characterized in that this method comprises the steps:
A, choose equally distributedly, every frame is divided into the equally distributed circular macro block that has common factor portion each other as the center of circle;
B, each circular macro block are that computing block is divided at the center with the center of circle; Said computing block is to be the center with the center of circle and to present centrosymmetric macro block with this center of circle;
C, calculate current macro left side common factor portion, go up common factor portion and right common factor portion the intermediate value of motion vector confirming every macroblock motion vector predicted value, and the first Halfway Stopping judging threshold T of definite computing block
1With the second Halfway Stopping judging threshold T
2Wherein, T
1=M*N; T
2=2*T
1, M wherein, N is the height and the width of computing block;
D, confirm that according to the abscissa of present frame macro block central point initial search frequency range is the corresponding macro block of the identical abscissa of former frame; Correspondence position point according to computing block in the motion vector computation initial search frequency range separately carries out
Computing, wherein I
c(i, the j) gray value of computing block pixel in the expression current macro, I
r((u v) is a motion vector, and M, N are the height and the width of computing block for i+u, the j+v) gray value of the corresponding pixel of the interior computing block of initial search frequency range in the preceding frame of expression;
E, judge that whether sad value is less than the first Halfway Stopping judging threshold T
1, if the motion vector that then this sad value is corresponding is as the final result of estimation; The minimum preceding frame macro block of sad value is just to decide matching module in the minimum initial search frequency range otherwise choose;
F, the centre coordinate of choosing the primary election matching module are that 45 ° of diagonal of starting point and its link to each other macro block as the binary search scope, carry out according to the correspondence position point of computing block in the motion vector computation binary search scope separately
Computing, whether the sad value of trying to achieve to each location point is less than the said second Halfway Stopping judging threshold T
2If the motion vector that then this sad value is corresponding is as the final result of estimation; Otherwise the macro block of choosing binary search scope SAD minimum value is selected matching module;
G, the corresponding motion vector of record sad value are the final result of estimation.
As optimization, the radius R of circular macro block
1Be adjacent macroblocks center distance W
1 
Further optimize, the computing block of each macro block is for being the center with the macro block center of circle, and width is (W
1-R
1) in length and breadth the symmetry square block.
In sum, the present invention program's advantage comprises:
1. have the macroblock partitions method of common factor between having adopted mutually, eliminated the phenomenon that occurs grid in existing most of video;
2. macro block is round shape, and the common factor area of adjacent macroblocks and borderline phase are together; Through adopting the motion vector of the part of occuring simultaneously between the macro block, and and then confirm the motion vector predictor of current macro through the intermediate value of calculating them, reacted the motion change between the macro block more really;
3. macro block is provided with computing block, and has adopted brand-new searching method, has improved efficient and a large amount of workloads that reduce compression processes of search, makes motion estimation more fast with accurate.
Description of drawings
Fig. 1 divides sketch map for existing video image macro-block;
Fig. 2 is a two field picture macroblock partitions sketch map of the present invention;
Fig. 3 is that common factor portion of the present invention and computing block are divided diagrammatic sketch;
Fig. 4 is that diagrammatic sketch amplifies in macro block and common factor portion;
Fig. 5 amplifies diagrammatic sketch for dividing macro block and common factor portion that computing block is arranged;
Fig. 6 is first hunting zone and direction of search diagrammatic sketch;
Fig. 7 is binary search scope and direction of search diagrammatic sketch;
Fig. 8 is a whole implementation flow chart of the present invention.
Embodiment
With reference to shown in Figure 1, be video image macro-block division methods common in the prior art.Two field picture is divided into the sub-piece of the equally distributed N*N pixel of two dimension, and General N is 16.According to existing motion estimation principle; Suppose the translational motion that all pixels works in every sub-block equate; The N*N piece of the preceding frame piece that search is mated with it most in portion's territory window of the corresponding sub-piece of former frame, the displacement of the match block of current sub-block and preceding frame on two dimensional surface is the motion vector that estimation obtains.
With reference to figure 2, be two field picture macroblock partitions method of the present invention, confirm at first that promptly some equally distributed points are centre point, be the center of circle with these points then, two field picture such as is divided at the rounded macro block of radius.If the square center with the 16*16 pixel size is the center of circle, then these centre point coordinates can be expressed as: (x, y) | x=8 (k+1), y=8 (k+1), k ∈ N}; Radius is:
the centre point coordinate can adjust according to the size of macro block.
With reference to figure 3, Fig. 4, macro block has common factor portion each other.When the centre point coordinate can be expressed as: (x, y) | x=8 (k+1), y=8 (k+1), k ∈ N}; Radius is: when
, each common factor portion just in time is four end points with the square of 16*16 pixel size.As shown in Figure 4, each common factor portion area equates, is representing the variation of four direction pixel value between the adjacent macroblocks respectively.
The contrast of the present invention and prior art, difference is different except division methods, the shape of macro block, exist the common factor portion between the macro block, at the evaluation method of current macro motion vector predictor.In the present invention, at first calculate current macro left side common factor portion 01, go up the motion vector of common factor portion 02 and right common factor portion 03, and be designated as W respectively
LU, W
U, W
R(like Fig. 3 and shown in Figure 4), then motion vector predictor is MVP
MED(u, v)=med{W
LU, W
U, W
R.When current macro does not have left common factor portion 01, W then
LU=(0,0); When not going up common factor portion 02, W then
U=(0,0); W then when not having right common factor portion 03
R=(0,0).Owing to left common factor portion 01, go up the variation that common factor portion 02 and right common factor portion 03 direct anti-shadow macro block, so be used as current macro motion prediction vector through their motion vector, the standard that more can improve motion estimation lacks degree.In addition, can be used as current macro motion prediction vector through the median of calculating common factor portion, principle is identical, no longer repeats.
Shown in figure 3 and 5, in the macro block of the present invention, also dividing has a computing block 04.Computing block 04 is relatively independent with common factor portion, really embodies the core of macro block characteristics.Like Fig. 5, computing block is to be the center with the center of circle and to present centrosymmetric macro block with this center of circle.When the centre point coordinate can be expressed as: (x, y) | x=8 (k+1), y=8 (k+1), k ∈ N}; Radius is:
The time, then computing block 04 does
The square of pixel.
Realize motion estimation, the another one major issue is that the reference macroblock of search speed and preceding frame is selected problem.In the present invention, different with existing three step search methods (3NSS), diamond search, hexagon motion search, melee shape method for searching motion, at first determine the first Halfway Stopping judging threshold T according to computing block
1With the second Halfway Stopping judging threshold T
2Method is: T
1=M*N; T
2=2*T
1, M wherein, N is the height and the width of computing block.
The first Halfway Stopping judging threshold T
1With the second Halfway Stopping judging threshold T
2After confirming, (be assumed to be (X according to present frame macro block central point
0, Y
0)) abscissa X confirm initial search frequency range; The method of confirming is the Y=Y of the preceding frame macro block central point searched for
0Corresponding macro block; Correspondence position point according to computing block in the motion vector computation initial search frequency range separately carries out
Computing, wherein I
c(i, the j) gray value of computing block pixel in the expression current macro, I
r((u v) is a motion vector, and M, N are the height and the width of computing block for i+u, the j+v) gray value of the corresponding pixel of the interior computing block of initial search frequency range in the preceding frame of expression; The direction of search of initial search frequency range can be according to the decision of motion-vector prediction direction, and as shown in Figure 6, if be deflection X coordinate, then the direction of search is by X
0Beginning is toward X＞X
0Search.In this search procedure, the sad value that the present frame macro block calculates is less than the first Halfway Stopping judging threshold T
1The motion vector that then this sad value is corresponding is as the final result of estimation and finish the motion estimation of retrieval and present frame, otherwise to being in 0-＞X
0Former frame macro block in the scope is searched for, and judges SAD, sad value is arranged less than the first Halfway Stopping judging threshold T
1The motion vector that then this sad value is corresponding is just to decide matching module as the final result of estimation otherwise choose the preceding frame macro block of minimum sad value.
After just deciding matching module and being determined because this hunting zone is confined to single direction, so in searching less than the first Halfway Stopping judging threshold T
1Preceding frame macro block the time, be necessary to carry out binary search at other coordinate direction.As shown in Figure 7, the centre coordinate of choosing the primary election matching module be starting point appear with it ± preceding frame macro block that 45 ° of diagonal link to each other is as the binary search scope.Can first+45 ° direction in the time of practical implementation ,-45 ° of directions in back are searched for then, and the correspondence position point according to computing block in the motion vector computation binary search scope separately in the search procedure carries out
Computing, whether the sad value of trying to achieve to each location point is less than the said second Halfway Stopping judging threshold T
2If the motion vector that then this sad value is corresponding is as the final result of estimation; Otherwise the macro block of choosing binary search scope SAD minimum value is selected matching module, and the piece matching value and the motion vector thereof of the selected matching module of record are the final result of estimation.
In sum, included the four direction of two coordinates of X-Y scheme in the scope of whole retrieval, the current macro motion-vector prediction is confirmed the initial direction of search simultaneously, according to the first Halfway Stopping judging threshold T
1With the second Halfway Stopping judging threshold T
2Accelerated the speed of search,, can reduce the scope of search, improved the accuracy and the validity of estimation according to this searching method.
With reference to figure 8, below, said above comprehensive whole flow process is done general description:
Like step S801, at first definite equally distributed point is done the center of circle;
Like step S802, be that benchmark is divided into two field picture the circular macro block with common factor portion with the center of circle;
Like step S803, divide computing block in the macro block;
Like step S804, calculate current macro left side common factor portion, go up the motion vector W of common factor portion and right common factor portion
LU, W
U, W
R
Like step S805, three motion vectors are got median and are confirmed the macroblock motion vector predicted value;
Like step S806 and S807, confirm the first Halfway Stopping judging threshold T
1With the second Halfway Stopping judging threshold T
2
Like step S808, the direction of initial ranging is confirmed in prediction according to macroblock motion vector;
Like step S809, the search former frame macro block identical with the Y coordinate of current macro central point;
Like step S810, calculate by the search macro block sad value;
Like step S811, judge that whether sad value is less than T
1, be that the motion vector that then this sad value is corresponding is retrieved as the final result and the end of estimation, accomplish the motion estimation of present frame; Otherwise get into step S812;
Like step S812, the preceding frame macro block of getting sad value minimum in the preliminary hunting zone is for just deciding matching module;
Like step S813, confirm and just decide the matching module central coordinate of circle to be positive and negative 45 and to spend diagonal and link to each other macro block as the binary search scope;
Like step S814, calculate secondary by the sad value of search macro block;
Like step S815, judge that whether sad value is less than T
2Be that the motion vector that then this sad value is corresponding is retrieved as the final result and the end of estimation, accomplish the motion estimation of present frame; Otherwise get into step S816;
Like step S816, choose binary search and be divided into the minimum preceding frame macro block of interior sad value for selecting matching module;
Like step S817, obtain the motion estimation result.
Claims (4)
1. a video data compression method for estimating that utilizes edge effect to carry out motion prediction is characterized in that this method comprises the steps:
A, choose equally distributedly, every frame is divided into the equally distributed circular macro block that has common factor portion each other as the center of circle;
B, each circular macro block are that computing block is divided at the center with the center of circle; Said computing block is to be the center with the center of circle and to present centrosymmetric macro block with this center of circle;
C, calculate current macro left side common factor portion, go up common factor portion and right common factor portion the intermediate value of motion vector confirming every macroblock motion vector predicted value, and the first Halfway Stopping judging threshold T of definite computing block
1With the second Halfway Stopping judging threshold T
2Wherein, T
1=M*N; T
2=2*T
1, M wherein, N is the height and the width of computing block;
D, confirm that according to the abscissa of present frame macro block central point initial search frequency range is the corresponding macro block of the identical ordinate of former frame; Correspondence position point according to computing block in the motion vector computation initial search frequency range separately carries out
Computing, wherein I
c(i, the j) gray value of computing block pixel in the expression current macro, I
r((u v) is a motion vector, and M, N are the height and the width of computing block for i+u, the j+v) gray value of the corresponding pixel of the interior computing block of initial search frequency range in the preceding frame of expression;
E, judge that whether sad value is less than the first Halfway Stopping judging threshold T
1, if the motion vector that then this sad value is corresponding is as the final result of estimation; The minimum preceding frame macro block of sad value is just to decide matching module in the minimum initial search frequency range otherwise choose;
F, the centre coordinate of choosing with the primary election matching module are end points, and be with it ± the frame macro block carries out according to the correspondence position point of computing block in the motion vector computation binary search scope separately as the binary search scope before 45 ° of diagonal link to each other
Computing judges that whether sad value that each location point tries to achieve is less than the said second Halfway Stopping judging threshold T
2If the motion vector that then this sad value is corresponding is as the final result of estimation; Otherwise the macro block of choosing binary search scope SAD minimum value is selected matching module;
G, the corresponding motion vector of record sad value are the final result of estimation.
2. video data compression method for estimating as claimed in claim 1 is characterized in that: the radius R 1 of circular macro block is adjacent macroblocks OC
3. according to claim 1 or claim 2 video data compression method for estimating, it is characterized in that: the computing block of each macro block is the square image block of symmetry in length and breadth for being the center with the macro block center of circle, and said computing block is relatively independent with said common factor portion.
4. video data compression method for estimating as claimed in claim 3 is characterized in that: initial search direction is identical with the horizontal component direction of motion-vector prediction.
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| CN1777289A (en) * | 2005-11-30 | 2006-05-24 | 天津大学 | Method for speeding up motion estimation utilizing selective prediction |
| CN1816146A (en) * | 2005-02-03 | 2006-08-09 | 联想(北京)有限公司 | Method for estimating motion vector in video frequency data compression |
| CN101184233A (en) * | 2007-12-12 | 2008-05-21 | 中山大学 | CFRFS based digital video compressed encoding method |
| CN101448161A (en) * | 2008-12-30 | 2009-06-03 | 上海广电（集团）有限公司中央研究院 | Motion estimation method |
| US7551673B1 (en) * | 1999-05-13 | 2009-06-23 | Stmicroelectronics Asia Pacific Pte Ltd. | Adaptive motion estimator |
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| CN100337482C (en) * | 2005-06-09 | 2007-09-12 | 上海交通大学 | Fast motion assessment method based on object edge shape |
| CN101090502B (en) * | 2006-06-13 | 2010-05-12 | 中兴通讯股份有限公司 | Controllable quick motion valuation algorithm for prediction quality |
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| US7551673B1 (en) * | 1999-05-13 | 2009-06-23 | Stmicroelectronics Asia Pacific Pte Ltd. | Adaptive motion estimator |
| CN1816146A (en) * | 2005-02-03 | 2006-08-09 | 联想(北京)有限公司 | Method for estimating motion vector in video frequency data compression |
| CN1777289A (en) * | 2005-11-30 | 2006-05-24 | 天津大学 | Method for speeding up motion estimation utilizing selective prediction |
| CN101184233A (en) * | 2007-12-12 | 2008-05-21 | 中山大学 | CFRFS based digital video compressed encoding method |
| CN101448161A (en) * | 2008-12-30 | 2009-06-03 | 上海广电（集团）有限公司中央研究院 | Motion estimation method |
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