CN102131094A - motion prediction method - Google Patents

Abstract

A motion prediction method, comprising: determining a plurality of candidate units corresponding to a current unit of a current frame; obtaining motion vectors of a plurality of candidate units; calculating time scaling factors of the candidate units according to the time distances between the reference frames and the current frames of the candidate units; scaling the motion vectors of the plurality of candidate units according to the time scaling factor to obtain scaled motion vectors; and selecting a motion vector predictor for motion prediction of the current unit from the plurality of candidate units according to the scaled motion vector. By the motion prediction method, the candidate set is adaptively determined according to the characteristics of the current unit, and the performance of motion prediction can be improved.

Description

motion prediction method

technical field

This invention relates to video processing and in particular to motion prediction of video data.

Background technique

The H.264 compression standard can provide excellent video quality at a much lower bit rate than previous standards by employing features such as sub-pixel accuracy and multiple-referencing. Video compression programs can usually be divided into five parts, including: inter-prediction/intra-prediction (inter-prediction/intra-prediction), transform/inverse-transform (transform/inverse-transform), quantization/inverse quantization (quantization/ inverse-quantization), loop filter, and entropy encoding. H.264 is used in various applications, such as Blu-ray Disc (Blu-ray Disc), DVB broadcast service, direct-broadcast satellite television (direct-broadcast satellite television) service, cable TV service, and real-time (real-time) video conferencing ( conferencing).

A video data stream consists of a sequence of frames. Each frame is divided into coding units (eg, macroblocks or extended macroblocks) for video processing. Each CU can be partitioned into quad-tree partitions, and the leaf CUs are called PUs. The PU can be further partitioned into quadtree partitions, and each partition is assigned a motion parameter. In order to reduce the cost of transmitting a large number of motion parameters, a motion vector predictor (motion vector predictor, hereinafter referred to as MVP) is calculated for each partition by referring to adjacent coded blocks, because the motion of adjacent blocks tends to have high spatial correlation (spatial correlation) ), so that the coding efficiency can be improved.

Please refer to FIG. 1 , which is a schematic diagram of a current (encoding) unit 100 and a plurality of adjacent (encoding) units A, B, C, and D. As shown in FIG. In this example, the current cell 100 is the same size as neighboring cells A, B, C, and D; however, the cells need not be the same size. The MVP of the current unit 100 is predicted from neighboring units A, B, and C or A, B, and D (if C is not available). When the current unit 100 is a 16×16 block and the motion vector of the neighboring unit C exists, the medium of the motion vectors of the neighboring units A, B, and C is determined as the MVP of the current unit 100 . When the current unit 100 is a 16×16 block and the motion vector of the neighboring unit C does not exist, the median value of the motion vectors of the neighboring units A, B, and D is determined as the MVP of the current unit 100 . When the current unit 100 is the 8×16 partition of the left half of the 16×16 block, the motion vector of the neighboring unit A is decided to be the MVP of the current unit 100 . When the current unit 100 is the 8×16 partition of the right half of the 16×16 block, the motion vector of the neighboring unit C is decided to be the MVP of the current unit 100 . When the current unit 100 is a 16×8 partition of the upper half of a 16×16 block, the motion vector of the neighboring unit B is determined to be the MVP of the current unit 100 . When the current unit 100 is the 16×8 partition of the lower half of the 16×16 block, the motion vector of the neighboring unit A is decided to be the MVP of the current unit 100 .

When the MVP of the current unit is predicted from the motion vectors of neighboring units A, B, C, and D, the motion vectors of neighboring units A, B, C, and D are not properly temporally zoom. For example, the reference frames of the neighboring units A, B, and C are different, and the motion vectors of the neighboring units A, B, and C respectively correspond to the aforementioned reference frames. The temporal distance between each reference frame and the current frame is different. Therefore, before predicting the MVP of the current unit 100 according to the motion vectors of the neighbors A, B, and C, the motion vectors of the neighbors A, B, and C should be temporally scaled according to the temporal distance.

The MVP of the current unit 100 is predicted only based on the motion vectors (motion vectors (hereinafter referred to as MV) of neighboring units A, B, C, and D). If more candidate MVPs are considered and the best candidate is selected through rate-distortion optimization, the prediction accuracy of MVP can be further improved. For example, motion vector competition (MVC) is proposed to select the best MVP from a predetermined set of candidates specified by a sequence level. The predetermined candidate set includes H.264 standard predictors (such as the median MV of adjacent units), the MV of collocated units, and the MV of adjacent units, where the position of the collocated unit in the reference frame Same as the current cell's position in the current frame. The number of MVPs in the recommended predetermined candidate set is two. The predetermined candidate set is fixed at the video sequence level according to the motion vector competition method.

Contents of the invention

In order to solve the above technical problems, the following technical solutions are provided:

An embodiment of the present invention provides a motion prediction method, including: determining a plurality of candidate units corresponding to the current unit of the current frame; obtaining motion vectors of the plurality of candidate units; Calculate the time scaling factor of the plurality of candidate units; according to the time scaling factor, scale the motion vectors of the plurality of candidate units to obtain the scaled motion vector; and according to the scaled motion vector, from the multiple candidate units A motion vector predictor is selected for motion prediction of the current unit.

The embodiment of the present invention further provides a motion prediction method, including: determining a candidate unit for motion prediction of the current unit; determining a coded unit corresponding to the current unit; and calculating a candidate unit corresponding to each of the coded units The motion difference between the motion vector and the motion vector of each of the coded units; according to a series of weights, the motion difference corresponding to each of the candidate units is added to obtain a plurality of a weighted sum of each of the units; and selecting at least one selected candidate unit for motion prediction of the current unit from the candidate units based on the weighted sum.

In the motion prediction method described above, the candidate set is adaptively determined according to the characteristics of the current unit, which can improve the performance of motion prediction.

Description of drawings

FIG. 1 is a schematic diagram of a current coding unit and multiple adjacent coding units.

Figure 2 is a block diagram of a video encoder according to one embodiment of the present invention.

Fig. 3 is a schematic diagram of scaling of motion vectors of two candidate units.

FIG. 4 is a flowchart of a motion prediction method with time difference adjustment.

FIG. 5 is a schematic diagram of multiple candidate units for motion prediction of a current unit according to an embodiment of the present invention.

6A and 6B are flowcharts of a motion prediction method with adaptively selected candidate units according to an embodiment of the present invention.

FIG. 7 is a schematic diagram of a table of recorded motion differences corresponding to different coded units and candidate units according to one embodiment of the present invention.

Detailed ways

Certain terms are used in the description and claims to refer to particular elements. Those skilled in the art should understand that hardware manufacturers may use different terms to refer to the same component. The specification and claims do not use the difference in name as a way to distinguish components, but use the difference in function of components as a criterion for distinguishing. The "comprising" mentioned in the description and the claims is an open term, therefore, it should be interpreted as "including but not limited to". Furthermore, the term "coupled" herein includes any direct and indirect means of electrical connection. Therefore, if it is described that the first device is coupled to the second device, it means that the first device may be directly electrically connected to the second device, or indirectly electrically connected to the second device through other devices or connection means.

Please refer to FIG. 2 , which is a block diagram of a video encoder 200 according to an embodiment of the present invention. In one embodiment, video encoder 200 includes motion prediction module 202 , subtraction module 204 , transform module 206 , quantization module 208 , and entropy encoding module 210 . Video encoder 200 receives a video input and produces as output a bitstream. The motion prediction module 202 performs motion prediction on the video input to generate prediction samples and prediction information. The subtraction module 204 then subtracts the predicted samples from the video input to obtain a residue, thereby reducing the video data amount of the video input to the residual video data amount. Then the residual is sent to the transform module 206 and the quantization module 208 sequentially. The transform module 206 performs a discrete cosine transform (DCT) on the residual to obtain a transformed residual. The quantization module 208 then quantizes the transformed residual to obtain a quantized residual. The entropy encoding module 210 then performs entropy encoding on the quantized residual and prediction information to obtain a bitstream as output.

The motion prediction module 202 predicts the MVP of the current unit of the current frame according to the motion vectors of the plurality of candidate units. In one embodiment, the candidate unit is a neighboring unit adjacent to the current unit. Before the motion prediction module 202 predicts the MVP of the current unit, the temporal distance between the reference frame of the candidate unit and the current frame is calculated, and the motion vector of the candidate unit is scaled according to the temporal distance. Please refer to FIG. 3 , which is a diagram illustrating the scaling of motion vectors of two candidate units 310 and 320 . The current frame k contains two candidate units for motion prediction of the current unit 300 : a first candidate unit 310 and a second candidate unit 320 . The first candidate unit 310 has a motion vector MV ₁ corresponding to the reference frame i, and a first time difference D _ik between the reference frame i and the current frame k is calculated. The second candidate unit 320 has a motion vector MV ₂ corresponding to the reference frame 1, and a second time difference D _lk between the reference frame 1 and the current frame k is calculated.

Then the target temporal distance _Djk between the target search frame j and the current frame k is calculated. The target search frame j is the selected reference frame. The target temporal distance D _jk is then divided by the first temporal distance D _ik , a first temporal scaling factor is calculated, and the motion vector MV ₁ of the first candidate unit 310 is multiplied by the first temporal scaling factor (D _jk /D _ik ) to A scaled motion vector MV ₁ ′ corresponding to the first candidate unit 310 is obtained. The target temporal distance D _jk is then divided by the second temporal distance D _lk , a second temporal scaling factor is calculated, and the motion vector MV ₂ of the second candidate unit 320 is multiplied by the second temporal scaling factor (D _jk /D _lk ) to A scaled motion vector MV ₂ ′ corresponding to the second candidate unit 320 is obtained. Thus, both the scaled motion vectors MV _{1 ′} and MV ₂ ′ are measured corresponding to the target search frame j, so the temporal distance difference factor is removed from the scaled motion vectors MV _{1 ′} and MV _{2 ′} . Then the motion prediction module 202 can predict the MVP of the current frame 300 according to the scaled motion vectors MV _{1 ′} and MV ₂ ′ of the candidate units 310 and 320 .

Please refer to FIG. 4 , which is a flowchart of a motion prediction method 400 with time difference adjustment. First, multiple candidate units for the current unit of the current frame are determined (step 402). The candidate unit and the current unit are blocks having the same size or a different size, and each of the above units may be a coding unit, a prediction unit, or a prediction unit partition. In one embodiment, the candidate units include the left unit A on the left of the current unit, the upper unit B above the current unit, the upper right unit C on the upper right of the current unit, and the upper left unit D on the upper left of the current unit. A plurality of motion vectors for the candidate units are then obtained (step 404). Then, multiple temporal scaling factors of the candidate unit are calculated according to the temporal distances between the multiple reference frames of the candidate unit and the current frame (step 406 ). In one embodiment, a plurality of temporal distances between the reference frame of the candidate unit and the current frame are first calculated, and the target temporal distance between the target search frame and the current frame is also calculated, and then are respectively passed through corresponding to the candidate unit The temporal distance divides the target temporal distance to obtain multiple temporal scaling factors corresponding to candidate units, as shown in Figure 3.

Then, the motion vectors of the candidate units are scaled according to the temporal scaling factor to obtain a plurality of scaled motion vectors (step 408). In one embodiment, the motion vectors of the candidate units are respectively multiplied by the time scaling factors of the candidate units to obtain the scaled motion vectors of the candidate units, as shown in FIG. 3 . A motion vector predictor for the current unit is then selected from the candidate units based on the scaled motion vector (step 410). In one embodiment, a median scaled motion vector is calculated from the scaled motion vectors (eg, the scaled motion vectors are sorted), and the median scaled motion vector is then selected from the scaled motion vectors as the MVP of the current unit.

When the motion prediction module 202 decides the MVP of the current unit according to the motion vector competition method, generally, only the motion vectors of the two candidate units decided at the sequence level are included in the candidate set for deciding the MVP of the current unit. In addition, the candidate set is not adaptively determined according to the characteristics of the current unit. If the candidate set is adaptively determined according to the characteristics of the current unit, the performance of motion prediction can be improved.

Please refer to FIG. 5 , which is a schematic diagram of multiple candidate units used for motion prediction of the current unit 512 according to an embodiment of the present invention. In this embodiment, the current unit 512 and the candidate unit are blocks with different sizes, for example, the current unit 512 is a 16x16 block and the candidate unit is a 4x4 block. In another embodiment, the size of the current and candidate cells can be the same or different, and the size can be 4x4, 8x8, 8x16, 16x8, 16x16, 32x32, or 64x64. In this embodiment, the motion vectors of the four candidate units A, B, C, and D of the current frame 502 can be used as candidates for determining the MVP of the current unit 512 . In addition, the position of the colocated unit 514 in the reference frame 504 is the same as the position of the current unit 512 in the current frame 502, and the motion vectors of multiple candidate units a~j adjacent to the colocated unit 514 or located in the colocated unit 514 are also Can be used as a candidate for determining the MVP of the current unit 512 .

The candidate unit A in the current frame 502 is the partition located on the left side of the current unit 512, the candidate unit B in the current frame 502 is the partition located above the current unit 512, and the candidate unit C in the current frame 502 is located at the top right of the current unit 512. The partition, and the candidate unit D in the current frame 502 is the partition located above and to the left of the current unit 512 . The candidate unit a in the reference frame 504 is the partition located on the left side of the collocated unit 514, the candidate unit b in the reference frame 504 is the partition located above the collocated unit 514, and the candidate unit c in the reference frame 504 is located at the top right of the collocated unit 514 For the partition, the candidate unit d in the reference frame 504 is the partition located at the upper left of the co-located unit 514 . In addition, the candidate unit e in the reference frame 504 is a partition located inside the co-located unit 514, the candidate units f and g in the reference frame 504 are partitions located on the right side of the co-located unit 514, and the candidate unit h in the reference frame 504 is located in the co-located unit 514 in the lower left partition, the candidate unit i in the reference frame 504 is the partition located below the collocated unit 514 , and the candidate unit j in the reference frame 504 is the partition located in the lower right of the collocated unit 514 . In one embodiment, the candidate set used to determine the MVP of the current unit 512 further includes a calculated motion vector, for example, a motion vector equal to the median of the motion vectors of candidate units A, B, and C, equal to the candidate unit The motion vector of the median of the motion vectors of A, B, and D, and the scaled MVP obtained by a method similar to that shown in FIG. 4 .

After a plurality of motion vectors corresponding to the current unit 512 are determined to be included in the candidate set, at least one motion vector is adaptively selected from the candidate set for motion prediction of the current unit 512 . Please refer to FIG. 6A and FIG. 6B . FIG. 6A and FIG. 6B are flowcharts of a motion prediction method 600 with adaptively selected candidate units according to an embodiment of the present invention. A number of coded units corresponding to the current unit 512 are determined (step 602). A number of candidate units corresponding to the current unit 512 are determined (step 603). The candidate set for the current unit 512 is selected from a plurality of motion vectors corresponding to the current unit 512 . Motion vectors may include one or a combination of motion vectors of coded partitions/blocks in the same frame, calculated motion vectors, and motion vectors in reference frames. In one embodiment, the candidate set corresponding to the current unit 512 shown in FIG. 5 includes the motion vectors of units A, B, C, and D in the current frame 502 and the motion vector of unit e in the reference frame 504 . The candidate set may be determined based on one or more of previous statistics, neighbor information, shape of the current unit, and position of the current unit. For example, multiple motion vectors corresponding to the current unit 512 are ranked according to neighbor information, and the top three motion vectors are selected to be included in the candidate set. The final MVP can be selected from the candidate set by motion vector competition method or other selection methods. In some embodiments, multiple motion vectors are sorted according to a selection order, and the selection order is determined by a weighted sum of motion differences. The motion difference is the difference between each motion vector predictor and the candidate unit's corresponding decoded motion vector (ie, real-time motion vector). The weight may be determined by the shape and position of the current cell, or the weight may be determined by the shape and position of neighboring blocks.

Please refer to FIG. 7 . FIG. 7 is a diagram illustrating a table of recorded motion differences corresponding to different coded units and candidate units according to an embodiment of the present invention. For example, assume that unit A is selected as the target coded unit. The motion difference D _A,A between the motion vectors of unit A and the candidate unit _A A to the left of unit A is calculated. The motion difference D _B, A between cell A and the motion vectors of the candidate cell B _A above cell A is also calculated. The motion difference _Dc, A between the motion vectors of cell A and the candidate cell _CA located above and to the right of cell A is also calculated. The motion difference _DD ,A between the motion vectors of unit A and the candidate unit _DA located above and to the left of unit A is also calculated. The motion difference D a,A between the motion vectors of cell A and the candidate cell a _A located to the left of the cell corresponding to _{cell A} is also calculated. Similarly, motion difference values D _b,A , . . . , D _j,A corresponding to coded unit A are also calculated. Then the calculated motion differences DA _{,A, DB,A,DC,A} , _DD,A,DA , _A , _{Db,A ,} ..., _Dj, corresponding to the coded unit A _A is recorded in the table shown in FIG. 7 . Then select the target coded unit B from the coded units (step 604), calculate the motion difference DA between the motion vector of the target coded unit B and the motion vectors of the plurality of candidate units corresponding to the target coded unit _{B, B} , D _{B , B} , D _{C , B} , D _{D , B} , D _{a , B} , D _{b , B} , ..., D _{j , B} (step 606) and record it in the table shown in Fig. 7 middle. Step 604 and step 606 are repeated until all coded units A, B, C, D, and e are selected as target coded units and corresponding to motion difference values of coded units A, B, C, D, and e have been calculated (step 608).

After the motion differences corresponding to the coded units A, B, C, D, and e have been calculated, the selection order of multiple motion vectors is determined by the weighted sum of the motion differences, and the target candidate unit is selected from the candidate units (step 610) . For example, if the candidate unit A is selected as the target candidate unit, according to a series of weights _WA , _WB , _WC , _WD , and _We will correspond to the motion difference D _{A, A of the target candidate unit A} , D _{A, B} , D _{A, C} , D _{A, D} , and D _{A, e} are added together to obtain the weighted sum S A corresponding to the target candidate unit _A = [(D _{A, A} × W _A )+( DA _{, B} ×W _B )+(DA _,C ×W _C )+(DA _,D ×W _D )+(DA _,e ×W _e )] (step 612), where the weights W _A , W _B , W _C , W _D , and We correspond to one of the encoded units A, B, C, D, and _e , respectively. Then other candidate units B, C, D, e, ..., i, and j are sequentially selected as target candidate units, corresponding to the weights of candidate units B, C, D, e, ..., i, and j and S _B , S _C , _SD , Se , _. . . , S _i , and S _j are sequentially calculated.

When all candidate units have been selected as target candidate units and correspond to the weighted sums _S A , S B , S _C , SD _of all candidate units A, _B , C, D, e, ..., i, and j , S _e , ... , S _i , and S _j have been calculated (step 614), according to the weighted sum S corresponding to candidate units A, B, C, D, e, ..., i, and j _A , S _B , S _C , _SD , _Se , ..., S _i , and S _j select at least one from candidate units A, B, C, D, e, ..., i, and j for Selected candidate units for motion prediction of the current unit (step 616). In one embodiment, the weighted sums S _A , S _B , S _C , _SD , _Se , ..., S _i , and S _j are sorted according to size, and correspond to the best weighted sums (according to different weighting methods The candidate unit which may be the smallest weighted sum or the largest weighted sum) is decided as the selected candidate unit. Finally, the motion vector of the current unit 512 is predicted based on the motion vectors of the selected candidate units.

Although the present invention has been disclosed above in a preferred embodiment, it is not intended to limit the present invention, and any person skilled in the art can make some changes without departing from the scope of the present invention, so the protection scope of the present invention The scope defined by the claims shall prevail.

Claims (18)

1. motion forecast method comprises:

Decision is corresponding to a plurality of candidate units of the active cell of present frame;

Obtain a plurality of motion vectors of these a plurality of candidate units;

According to a plurality of reference frames of these a plurality of candidate units and a plurality of time gaps between this present frame, calculate a plurality of time-scaling factors of these a plurality of candidate units;

According to these a plurality of time-scaling factors, a plurality of motion vectors of this of these a plurality of candidate units of convergent-divergent are to obtain the motion vector of a plurality of convergent-divergents; And

According to the motion vector of these a plurality of convergent-divergents, be used for motion vector prediction of the motion prediction of this active cell from these a plurality of candidate units selections.

2. motion forecast method as claimed in claim 1 is characterized in that, this motion forecast method more comprises:

According to this motion vector of this motion vector prediction, predict the motion vector of this active cell.

3. motion forecast method as claimed in claim 1 is characterized in that, the calculation procedure of a plurality of time-scaling factors of this of these a plurality of candidate units more comprises:

Calculate these a plurality of reference frames of this a plurality of motion vectors of these a plurality of candidate units and a plurality of time gaps between this present frame;

Calculate the object time distance between target search frame and this present frame; And

Divide this object time distance by these a plurality of time gaps respectively, to obtain this a plurality of time-scaling factors.

4. motion forecast method as claimed in claim 3 is characterized in that, the convergent-divergent step of a plurality of motion vectors of this of these a plurality of candidate units more comprises:

These a plurality of motion vectors of these a plurality of candidate units be multiply by these a plurality of time-scaling factors of this a plurality of candidate units respectively, with the motion vector of these a plurality of convergent-divergents of obtaining these a plurality of candidate units.

5. motion forecast method as claimed in claim 1 is characterized in that, the selection step of this motion vector prediction more comprises:

Motion vector from the motion vector calculation intermediate value convergent-divergent of these a plurality of convergent-divergents;

To be this motion vector prediction corresponding to this candidate unit decision of the motion vector of this intermediate value convergent-divergent.

6. motion forecast method as claimed in claim 1, it is characterized in that these a plurality of candidate units comprise last unit, the top-right upper right unit of this active cell and the upper left upper left unit of this active cell of top of left unit, this active cell on the left side of this active cell.

7. motion forecast method as claimed in claim 1 is characterized in that, this active cell is piece or macro block with these a plurality of candidate units.

8. motion forecast method comprises:

Decision is used for a plurality of candidate units of the motion prediction of active cell;

Decision is corresponding to a plurality of coding units of this active cell;

Calculating corresponding in these a plurality of coding units each a plurality of motion vectors of these a plurality of candidate units and a plurality of motion differences between each the motion vector in this a plurality of coding units;

According to a series of a plurality of weights, will be corresponding to each this a plurality of motion difference addition in these a plurality of candidate units, to obtain a plurality of each weighted sums that correspond respectively in these a plurality of candidate units; And

According to these a plurality of weighted sums, select at least one selected candidate unit that is used for the motion prediction of this active cell from these a plurality of candidate units.

9. motion forecast method as claimed in claim 8 is characterized in that, this motion forecast method more comprises:

According to this motion vector of this selected candidate unit, predict the motion vector of this active cell.

10. motion forecast method as claimed in claim 8 is characterized in that, the calculation procedure of these a plurality of motion differences more comprises:

From these a plurality of select targets of coding unit coding unit;

Calculating is corresponding to these a plurality of motion differences between this motion vector of these a plurality of motion vectors of these a plurality of candidate units of this target coding unit and this target coding unit; And

Repetition is corresponding to the selection of this target of this target coding unit coding unit and the calculation procedure of these a plurality of motion differences, up to whole this target coding units that have been selected as of these a plurality of coding units.

11. motion forecast method as claimed in claim 8 is characterized in that, the addition step of these a plurality of motion differences more comprises:

From these a plurality of candidate unit select target candidate units;

According to these a plurality of weights of this series, will be corresponding to this a plurality of motion difference addition of this target candidate unit, to obtain this weighted sum corresponding to this target candidate unit; And

Repetition is corresponding to the selection of this target candidate unit of this target candidate unit and the addition step of these a plurality of motion differences, up to whole this target candidate unit that have been selected as of these a plurality of candidate units.

12. motion forecast method as claimed in claim 11 is characterized in that, these a plurality of weights correspond respectively to of these a plurality of coding units.

13. motion forecast method as claimed in claim 8 is characterized in that, the selection step of these a plurality of selected candidate units more comprises:

To these a plurality of weighted sum orderings; And

Will corresponding to optimum weighting and this candidate unit be chosen as this selected candidate unit.

14. motion forecast method as claimed in claim 8, it is characterized in that, these a plurality of coding units comprise the last unit, the top-right upper right unit of this active cell, the upper left upper left unit and the same bit location of this active cell of top of left unit, this active cell on the left side of this active cell, wherein should be identical with the position of this active cell in present frame with the position of bit location in reference frame.

15. motion forecast method as claimed in claim 8, it is characterized in that these a plurality of candidate units comprise last unit, the top-right upper right unit of this active cell and the upper left upper left unit of this active cell of top of left unit, this active cell on the left side of this active cell.

16. motion forecast method as claimed in claim 15, it is characterized in that, these a plurality of candidate units more comprise in first value cell in the value cell and second, wherein this in first the motion vector of value cell equal this unit, left side, the intermediate value of the motion vector of unit and this upper right unit on this, and this in second the motion vector of value cell equal this unit, left side, the intermediate value of the motion vector of unit and this upper left unit on this.

17. motion forecast method as claimed in claim 15, it is characterized in that, identical with the position of bit location in reference frame with the position of this active cell in present frame, and these a plurality of candidate units more comprise this left co-ordinated unit with the left side of bit location, be somebody's turn to do last same bit location with the top of bit location, should be with the top-right upper right same bit location of bit location, should be with the upper left upper left same bit location of bit location, this same bit location, be somebody's turn to do right same bit location with the right of bit location, be somebody's turn to do the same bit location in lower-left with the lower left of bit location, be somebody's turn to do following same bit location with the bottom of bit location, and should be with the same bit location in bottom-right bottom right of bit location.

18. motion forecast method as claimed in claim 8 is characterized in that, this active cell is piece or macro block with these a plurality of candidate units.

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