Abstract:
A soft windowing technique involves the use of a window for vector assisted frame differing, the window being larger than a macroblock of the structure defined over the video picture. The edges of each window taper so that overlapping windows provide the correct pixel weighting at the edges. For a scheme having 16*16 luminance macroblocks and 8*8 chrominance macroblocks, the luminance window is 24*24 and the chrominance window is 12*12.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     This invention relates to video compression methods and apparatus, in particular in the context of motion vector compensation techniques. 
     2. Description of the Prior Art 
     One digital compression standard, known as MPEG, was devised by and named after the Motion Picture Experts Group of the International Standards Organisation (ISO). In one form, known as MPEG1, early versions of the draft standard made use of forward prediction between past and current frames of a video signal. In later forms of MPEG1 and another known as MPEG2, the standard additionally makes use of bidirectional prediction, namely a combination of forward and backward prediction with the prediction made as an average of the forward and backward predictive frames. 
     Further details of the MPEG standard are set out in ISO/IEC 11172-2:1993(E) “Information Technology—Coding of Moving Pictures and Associated Audio for Digital Storage Media at up to about 1.5 Mbit/s”. 
     The use of motion compensation is an important aspect of MPEG coding. Motion compensation aims to minimize the error signal in difference frames by compensating for inter-frame movement. The process of motion compensation involves two separate processes: 
     i) Motion Vector Estimation (MVE); in which the motion offset between a frame pair is calculated; and 
     ii) Motion Vector Compensation (MVC); which uses the results of the MVE calculations to produce a difference signal with minimum artifacts. 
     There are several aspect of MVE and MVC which must be considered such as: 
     i) The type of motion permitted. In MPEG and other similar systems, the type of motion is limited simply to translational vectors in the ‘X’ and ‘Y’ axes. Researchers working in other fields have used other motion types, such as rotation, skew and size. The benefits of this work are not clear since using more complex shape matching may reduce the signal in the difference picture, but requires more data to transmit the shape parameters. 
     ii) The size of the macroblock is a compromise between smaller blocks having better coding efficiency but higher macroblock data rate, and larger blocks having worse coding efficiency but lower macroblock data rate (where a macroblock is the block size used for motion estimation and compensation). 
     iii) How to combine the results from Luminance (Y) and Chrominance (C) block matching. If completely separate vectors are used for Y and C motion vectors, the macroblock data rate will be doubled and there may be the possibility of picture disturbances created by poor matching of Y and C vectors. Combining the Y and C vectors will result in a lower macroblock data rate but the coding efficiency may drop slightly. 
     iv) The use of sub-pixel estimation and compensation. Often, motion between frames does not appear at integer pixel distances so some form of sub-pixel MVE and MVC will be beneficial. More vector data is generated to be transmitted/recorded and the data increase is very small but simple half-pixel estimation requires at least four times the computational power of a pixel based estimator and this must be considered. 
     There is a need for further developments in motion compensation coding with emphasis on low bit-rate systems in the range 64 Kbps to 2 Mbps. 
     SUMMARY OF THE INVENTION 
     It is an object of the invention to provide a video compression method involving motion vector compensation in which the problem of macroblock size compromise is alleviated. 
     It is another object of the invention to provide a video compression method involving motion vector compensation which is applicable to low bit-rate systems. 
     According to the invention there is provided a video compression method involving motion vector compensation, the method comprising: 
     defining a macroblock structure over a video picture to which motion vector analysis may be applied; and 
     applying a soft window to the macroblock structure such that adjacent windows overlap, with the edges of each window forming progressively increasing pixel weightings from the edge inwards, the soft window being larger than each macroblock in the structure. 
     The pixel weightings are preferably selected so that each overlapped pixel arising from overlapping windows has a summed weighting equal to a constant. 
     The soft window is preferably 50% larger in each dimension than a macroblock of the structure, and the tapering part of each window edge preferably comprises one third of the total length. Where the macroblock sizes differ for chrominance and luminance, the window sizes may differ proportionately. 
     In a preferred embodiment of the invention, the window with soft edges provides motion compensation with much better results on many types of test material. Although errors at higher video data rates may not be so visible, applying the window still leads to a general reduction in picture distortions. The window is simple to apply and the window coefficients (or weightings) are easy to use. 
     The above, and other objects, features and advantages of this invention will be apparent from the following detailed description of illustrative embodiments which is to be read in connection with the accompanying drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 shows a sample grid of luminance and chrominance components; 
     FIG. 2 shows a rounding process used for chrominance vector estimation; 
     FIG. 3 shows the use of interpolation filters to create sub-pixel vectors; 
     FIG. 4 shows window functions for luminance and chrominance macroblocks; and 
     FIG. 5 shows overlay of the motion vector windows in one and two dimensions. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Three sizes of picture have been used with motion compensation; 
     i) ‘VID’files: 720*576 pixels (and 704*576), with a target bit rate of around 4 Mbps. 
     ii) ‘SIF’ files: 352*288 pixels with a target bit rate of around 1 Mbps (video only) and 
     iii) ‘QIF’ files: 176*144 pixels with a target bit rate of around 220 Kbps (video only). 
     In each case, the chrominance pixel size is half in each axis for each component. 
     Experiments have been conducted to find the optimum macroblock size for each of the above systems. In each case the position was clear in that a macroblock size of 16*16 pixels for luminance and 8*8 for each chrominance produced the best results. In all three cases above, smaller macroblocks such as 8*8 for Y and 4*4 for C resulted in too much vector data, and larger macroblocks such as 24*24 for Y and 12*12 for C resulted in low levels of macroblock data but high error signals in the difference pictures. In this respect MPEG has correctly set the optimum motion vector block size. 
     The vector data to be transmitted depends on the picture size, but the following calculations were used as a guide to the data rate required for vector transmission: 
     Case 1: ‘VID’ files, 720*576 pixels 
     Number of macroblocks=45*36=1620 per frame 
     Assuming the logarithmic temporal decimation structure and for Y data a vector range limit of +/−31 pixels/frame, for an 8-Frame GOP (group of pictures): 
     
       
         
               
               
               
               
               
               
               
             
               
               
             
               
             
           
               
                   
               
               
                 No of Frames 
                 Vector Range 
                 Bits 
                 +&amp;− 
                 H&amp;V 
                 Y&amp;C 
                 Total Bits 
               
               
                   
               
             
             
               
                 4 
                 +/−31 
                 6 
                 *2 
                 *2 
                 *2 
                 192 
               
               
                 2 
                 +/−63 
                 7 
                 *2 
                 *2 
                 *2 
                 112 
               
               
                 1 
                 +/−127 
                 8 
                 *2 
                 *2 
                 *2 
                  64 
               
             
          
           
               
                 TOTAL BITS/GOP-MACROBLOCK: 
                 368 
               
             
          
           
               
                 The total vector bit rate is then 368*25/8*1620 = 1.863 Mbps 
               
               
                   
               
             
          
         
       
     
     Assuming that entropy coding can lower this by about 50%, then the overall vector bit rate can be reduced to around 900 Kbps. As mentioned in the introduction, if the Y and C vectors are combined, then this data rate can be further reduced to around 500 Kbps. More about the method of combination will follow in the next section. 
     Case 2: ‘SIF’ files, 352*288 pixels 
     Number of macroblocks=22*18=396 per frame 
     Similar calculations to VID picture coding follow, bearing in mind that the vector range limit can be reduced to +/−15 pixels/frame: 
     
       
         
               
               
               
               
               
               
               
             
               
               
             
               
             
           
               
                   
               
               
                 No of Frames 
                 Vector Range 
                 Bits 
                 +&amp;− 
                 H&amp;V 
                 Y&amp;C 
                 Total Bits 
               
               
                   
               
             
             
               
                 4 
                 +/−15 
                 5 
                 *2 
                 *2 
                 *2 
                 160 
               
               
                 2 
                 +/−31 
                 6 
                 *2 
                 *2 
                 *2 
                  96 
               
               
                 1 
                 +/−63 
                 7 
                 *2 
                 *2 
                 *2 
                  56 
               
             
          
           
               
                 TOTAL BITS/GOP-MACROBLOCK: 
                 312 
               
             
          
           
               
                 The total vector bit rate is then 312*25/8*396 = 386.1 Kbps 
               
               
                   
               
             
          
         
       
     
     With entropy coding and Y/C vector combination, this can be reduced to around 100 Kbps. 
     Case 3: ‘SIF’ files, 176*144 pixels 
     Number of macroblocks=11*9=99 per frame 
     For ‘QIF’ coding, and using a vector range limit as for SIF pictures because motion errors are much more critical with such a low resolution source, then the total vector bit rate becomes; 
     
       
         312*25/8*99=96.5 KbDs 
       
     
     which, with entropy reduction and Y/C vector combination, reduces to around 25 Kbps. 
     In each case above, the vector data rate is around 10% of the total required bit rate which is a reasonable allowance and not a level at which the motion vectors would severely limit the primary coding method. The use of macroblocks at a quarter of the size used above would increase the vector data rate to around 40% of the total data rate and become a severe overhead to the coding efficiency. The benefit gained by the use of quarter sized macroblocks is less than the quality loss resulting in the main coding area. Likewise, use of larger macroblocks reduces the vector data rate but only gains a small benefit for other coding areas. Such large macroblocks result in larger difference picture errors which cannot be so easily compensated in the remaining coding elements. 
     The use of sub-pixel vectors will require a small amount of extra data equivalent to an extra 14 bits per macroblock-G OP. 
     It has been mentioned that sending separate vectors for Y and C is wasteful of data bandwidth and could lead to misalignment of luminance and colour information. It is a commonly observed fact that the motion vectors of the chrominance components almost always follow the luminance component. There are exceptions, but these are very rare. Furthermore, the B-Y and R-Y components tend to have the same motion vectors. Therefore, a set of three vectors can easily be reduced to one by this simple assumption. 
     The problem with this assumption is a result of the nature of the chroma sub-sampling. Each chrominance component has half the sampling rate of the luminance component, leading to the sampling grid shown in FIG.  1 . 
     Then, if a vector value has an odd luminance pixel value, there is a rounding problem in the chrominance vector value since the vector does not point directly to a chrominance pixel site. At first it may seem that simple rounding could be applied, and first experiments used this. However, it was found in subsequent tests that the choice of round-up or round-down resulted in a significant performance change for the chrominance coding. The rounding must be selected on a macroblock basis, and since there are two axes for the vectors, there are several rounding combinations as shown in FIG.  2 . 
     In the first case, as shown in FIG. 2, where the horizontal vector is even valued and the vertical vector is odd valued, then the horizontal chrominance vector is simply half the luminance vector. However, the odd valued vertical vector can be rounded either up or down as indicated in the figure. Likewise for the second case where the vertical vector is even valued and the horizontal vector is odd valued. In this case, the horizontal rounding can be either up or down as indicated. In the last case, both horizontal and vertical vectors are odd valued resulting in four possible rounding options as shown. 
     The method of dynamically rounding on a macroblock basis could be avoided if the chrominance data were interpolated to the same size as the luminance data; however, this is expensive and uses extra memory. This alternative method works well and can be simply implemented by adding one extra bit to each luminance vector. If the bit is zero, then the rounding of the chrominance vector is ‘down’; if the bit is one, then the rounding is ‘up’. This small overhead will cover all the options shown in FIG.  2  and is a much lower overhead than that required to send independent chrominance vector data. Note that the technique is applied to both MVE and MVC processes. 
     A further issue concerns the relationship between the scaling of Y and C values to generate the MSE (or MAD) values for MVE. Both Y and C are used since the vector will represent both components and where, for example, block matching of the luminance component may show little difference, the chrominance difference value may hold the balance of vector selection. In various experiments, the ratio did not seem to be critical and both the following expressions were used for vector selection at various points in the project timescale: 
     
       
           MSE ( a )=( Y   e ) 2 +( C   e ) 2   
       
     
     
       
           MSE ( b )=( Y   e ) 2 +2*( C   e ) 2   
       
     
     Since there seems to be little benefit for either, the first case is to be recommended because of its simplicity. 
     In experiments conducted to assess the benefits of sub-pixel MVE and MVC, only ½ pixels have been considered. Using ‘VID’ files presents a problem in that the video is interlaced and the question arises as to the best method of vertical interpolation. Horizontal interpolation is not a problem. 
     Using ‘SIF’ and ‘QIF’ picture sources presents a simple linear interpolation process since both are effectively frame based progressively scanned at 25 frames per second. However, the filter order becomes an important issue as the pixel sizes reduce since the filter ringing artifacts become increasingly visible. 
     All interpolation filters have been based on half-band filters. Four types were used offering increasing tap lengths and sharper transition bands as follows: 
     
       
         
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                   
               
             
             
               
                 1) 
                   
                   
                   
                   
                   
                   
                  1 
                  2 
                  1 
                   
                   
                   
                   
                   
                   
                   
               
               
                 2) 
                   
                   
                   
                   
                  −1 
                 0 
                  9 
                 16 
                  9 
                 0 −1 
               
               
                 3) 
                   
                   
                  3 
                 0 
                 −16 
                 0 
                  77 
                   
                 128 
                  77 
                 0 
                 −16 
                 0 
                  3 
               
               
                 4) 
                 −6 
                 0 
                 26 
                 0 
                 −79 
                 0 
                 315 
                   
                 512 
                 315 
                 0 
                 −79 
                 0 
                 26 
                 0 
                 −6 
               
               
                   
               
             
          
         
       
     
     These filters will be referred to as respectively 1, 2, 3 and 4. 
     The first test results Used ‘VID’ pictures compressed using the 2-frame ‘SX’ system using alternate ‘I’ and ‘B’ frames. These results show the effects of applying first horizontal interpolation, only, then horizontal and vertical interpolation where the vertical interpolation was applied to a frame (rather than a field). 
     
       
         
               
             
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Sub-Pixel Motion Compensation Using Different Methods 
               
             
          
           
               
                 Frame Number: 
                 1 
                 3 
                 5 
                 7 
                 9 
                 11 
                 13 
                 15 
                 17 
                 19 
               
               
                   
               
             
          
           
               
                 No 
                 Y mse 
                 7.3841 
                 6.9818 
                 6.4252 
                 7.7629 
                 7.4938 
                 7.0807 
                 9.8862 
                 8.0370 
                 10.001 
                 8.7079 
               
               
                 Interpolation 
                 C mse 
                 2.7787 
                 2.5288 
                 2.7253 
                 2.6123 
                 2.3503 
                 2.2419 
                 2.0432 
                 1.8610 
                 1.8340 
                 1.9962 
               
               
                   
                 Y S/N 
                 36.69 
                 36.65 
                 36.72 
                 36.64 
                 36.64 
                 36.66 
                 36.56 
                 36.48 
                 36.55 
                 36.51 
               
               
                   
                 C S/N 
                 37.31 
                 37.24 
                 37.32 
                 37.35 
                 37.27 
                 37.29 
                 37.18 
                 37.06 
                 37.07 
                 37.02 
               
               
                   
                 Y bpp 
                 1.4937 
                 1.4935 
                 1.4622 
                 1.5349 
                 1.5334 
                 1.4951 
                 1.6676 
                 1.5773 
                 1.6626 
                 1.5910 
               
               
                   
                 C bpp 
                 0.4685 
                 0.4565 
                 0.4641 
                 0.4581 
                 0.4465 
                 0.4469 
                 0.4358 
                 0.4273 
                 0.4278 
                 0.4281 
               
               
                   
                 Σ bpp 
                 1.9622 
                 1.9500 
                 1.9263 
                 1.9930 
                 1.9799 
                 1.9420 
                 2.1034 
                 2.0046 
                 2.0904 
                 2.0191 
               
               
                 Horizontal 
                 Y mse 
                 7.1965 
                 6.6262 
                 6.0303 
                 7.525 
                 7.2961 
                 7.7389 
                 6.3086 
                 5.8330 
                 5.4225 
                 7.3818 
               
               
                 Interpolation 
                 C mse 
                 1.9811 
                 1.9371 
                 1.8813 
                 1.9883 
                 1.9111 
                 1.8585 
                 2.0060 
                 1.7843 
                 1.9985 
                 1.9191 
               
               
                 Only 
                 Y S/N 
                 36.67 
                 36.65 
                 36.73 
                 36.63 
                 36.63 
                 36.60 
                 36.67 
                 36.78 
                 36.80 
                 36.67 
               
               
                   
                 C S/N 
                 37.41 
                 37.32 
                 37.41 
                 37.43 
                 37.34 
                 37.34 
                 37.18 
                 37.06 
                 37.06 
                 37.03 
               
               
                   
                 Y bpp 
                 1.4981 
                 1.4905 
                 1.4527 
                 1.5448 
                 1.5417 
                 1.5707 
                 1.4453 
                 1.3969 
                 1.3810 
                 1.4948 
               
               
                   
                 C bpp 
                 0.4102 
                 0.4108 
                 0.4077 
                 0.4089 
                 0.4075 
                 0.4107 
                 0.4268 
                 0.4217 
                 0.4333 
                 0.4244 
               
               
                   
                 Σ bpp 
                 1.9083 
                 1.9013 
                 1.8604 
                 1.9537 
                 1.9492 
                 1.9814 
                 1.8721 
                 1.8186 
                 1.8143 
                 1.9192 
               
               
                 Horizontal 
                 Y mse 
                 7.5413 
                 7.2948 
                 6.8039 
                 8.0667 
                 7.9487 
                 8.2087 
                 6.4070 
                 6.0407 
                 5.4421 
                 7.7807 
               
               
                 and 
                 C mse 
                 1.8764 
                 1.9113 
                 1.9978 
                 1.9651 
                 1.8879 
                 1.8651 
                 2.0660 
                 1.8445 
                 2.0226 
                 1.8970 
               
               
                 Vertical 
                 Y S/N 
                 36.68 
                 36.65 
                 36.73 
                 36.64 
                 36.64 
                 36.61 
                 36.67 
                 36.78 
                 36.80 
                 36.69 
               
               
                 Interpolation 
                 C S/N 
                 37.42 
                 37.34 
                 37.43 
                 37.44 
                 37.34 
                 37.36 
                 37.19 
                 37.07 
                 37.06 
                 37.03 
               
               
                   
                 Y bpp 
                 1.5114 
                 1.5133 
                 1.4843 
                 1.5674 
                 1.5645 
                 1.5930 
                 1.4547 
                 1.4070 
                 1.3840 
                 1.5059 
               
               
                   
                 C bpp 
                 0.4099 
                 0.4089 
                 0.4083 
                 0.4094 
                 0.4054 
                 0.4087 
                 0.4269 
                 0.4213 
                 0.4324 
                 0.4230 
               
               
                   
                 Σ bpp 
                 1.9213 
                 1.9222 
                 1.8926 
                 1.9768 
                 1.9699 
                 2.0017 
                 1.8816 
                 1.8283 
                 1.8164 
                 1.9289 
               
               
                   
               
             
          
         
       
     
     The horizontal filter was set to type 3 and the vertical to type 1. The results are shown in Table 1 for a system with the following parameters: 
     Source Picture: Mobile &amp; Calendar, frames 0-20 
     Compression type: I-B, 2-frame with 3-stage Wavelet Spatial Decimation 
     Quantisation: Q=1070, Quantiser Viewing Height=3H 
     From this table, it can be clearly seen that the addition of horizontal sub-pixel motion compensation is worthwhile leading to significant drops in the overall bit rate (whilst S/N remains similar). However, the addition of vertical sub-pixel motion compensation adds nothing, indeed makes the performance worse. The benefits of vertical sub-pixel motion compensation are, therefore, difficult to justify for an interlaced scan picture source. 
     However, SIF and QIF pictures are frame based and do not have any problems with interlace. In experiments on both types of picture source, the application of sub-pixel motion compensation is equally valid in both the horizontal and vertical directions and as such the same filters are used for interpolation in both axes. 
     The second set of results were a rather more comprehensive comparison of pixel and sub-pixel motion compensation based on the use of SIF pictures coded at 0.4 bpp (˜1 Mbps) based on an 8 frame GOP with Wavelet Spatial Decimation. Results are given in Table 2 below. 
     
       
         
               
             
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Results of Pixel and Sub-pixel based Motion Vector Compensation for 1 Mbps SIF Pictures 
               
             
          
           
               
                 Vector Type: 
                 Integer Motion Vectors 
                 Sub-Pixel Motion Vectors 
               
             
          
           
               
                 Sequence 
                 Q 
                 Y S/N 
                 C S/N 
                 Y bpp 
                 C bpp 
                 Σbpp 
                 Q 
                 Y S/N 
                 C S/N 
                 Y bpp 
                 C bpp 
                 Σbpp 
               
               
                   
               
             
          
           
               
                 Mobile 
                 0-8 
                 185 
                 27.57 
                 29.69 
                 .3363 
                 .1065 
                 .3895 
                 220 
                 28.94 
                 30.76 
                 .3356 
                 .1241 
                 .3976 
               
               
                 &amp; 
                  8-16 
                 185 
                 27.61 
                 29.69 
                 .3328 
                 .1073 
                 .3864 
                 215 
                 28.74 
                 30.64 
                 .3285 
                 .1234 
                 .3902 
               
               
                 Calendar 
                 16-24 
                 205 
                 28.54 
                 30.28 
                 .3305 
                 .1195 
                 .3902 
                 230 
                 29.32 
                 31.12 
                 .3327 
                 .1254 
                 .3954 
               
               
                 Renata 
                 0-8 
                 280 
                 31.60 
                 35.83 
                 .3655 
                 .0659 
                 .3984 
                 300 
                 32.04 
                 36.10 
                 .3645 
                 .0700 
                 .3995 
               
               
                   
                  8-16 
                 270 
                 31.24 
                 35.53 
                 .3568 
                 .0643 
                 .3889 
                 280 
                 31.53 
                 35.63 
                 .3510 
                 .0660 
                 .3840 
               
               
                   
                 16-24 
                 290 
                 31.44 
                 35.69 
                 .3637 
                 .0631 
                 .3952 
                 310 
                 31.89 
                 36.01 
                 .3672 
                 .0706 
                 .4025 
               
               
                 Football 
                 0-8 
                 450 
                 37.28 
                 39.49 
                 .3596 
                 .0677 
                 .3934 
                 490 
                 37.91 
                 39.90 
                 .3614 
                 .0745 
                 .3986 
               
               
                   
                  8-16 
                 415 
                 36.52 
                 38.72 
                 .3629 
                 .0576 
                 .3917 
                 470 
                 37.37 
                 39.35 
                 .3615 
                 .0652 
                 .3927 
               
               
                   
                 16-24 
                 320 
                 33.88 
                 36.63 
                 .3633 
                 .0578 
                 .3922 
                 360 
                 34.63 
                 37.23 
                 .3601 
                 .0674 
                 .3938 
               
               
                 Susie 
                 0-8 
                 1170  
                 43.46 
                 45.50 
                 .3509 
                 .0846 
                 .3932 
                 1420  
                 44.75 
                 46.21 
                 .3497 
                 .1006 
                 .4000 
               
               
                   
                  8-16 
                 1160  
                 43.48 
                 45.48 
                 .3550 
                 .0839 
                 .3969 
                 1410  
                 44.60 
                 46.25 
                 .3459 
                 .1016 
                 .3967 
               
               
                   
                 16-24 
                 1095  
                 42.98 
                 45.31 
                 .3475 
                 .0744 
                 .3847 
                 1300  
                 44.37 
                 46.04 
                 .3546 
                 .0911 
                 .4001 
               
               
                   
                 24-32 
                 980 
                 42.59 
                 44.96 
                 .3578 
                 .0668 
                 .3912 
                 1140  
                 43.60 
                 45.46 
                 .3541 
                 .0760 
                 .3921 
               
               
                   
                 32-40 
                 800 
                 42.10 
                 44.34 
                 .3559 
                 .0698 
                 .3908 
                 810 
                 42.32 
                 44.32 
                 .3587 
                 .0672 
                 .3923 
               
               
                   
                 40-48 
                 890 
                 43.67 
                 44.99 
                 .3434 
                 .1028 
                 .3948 
                 900 
                 43.74 
                 45.07 
                 .3416 
                 .1026 
                 .3929 
               
               
                   
               
             
          
         
       
     
     Note 1: the calculation of the sum bit rate is Y+C/2 since the chrominance only has half the number of pixels compared to luminance. 
     Note 2: the interpolation filter was of type 4 (the most complex) for both horizontal and vertical axes. 
     The results show a clear benefit of using sub-pixel vectors; rather clearer than the earlier example, and where the use of sub-pixel motion vectors produces a visible improvement in picture quality in viewing tests. 
     Tests of QIF coding always used sub-pixel motion vector compensation since all available methods were required to make any useful results available at the low bits-per-pixel targeted for this application. Hence no comparative measurements are available for QIF coding. 
     The investigations of the previous section revealed an anomaly in the philosophy of motion vector estimation as currently performed. It was not clear whether this would affect coding performance. 
     The anomaly only affects ‘B’ frames, not ‘P’ frames. Each ‘B’ frame has associated a pair of motion vectors, one pointing to the frame behind in time, the other pointing to a frame in advance. The selection of the vectors is made by comparing the macroblock of the current frame with a macroblock in another frame, but offset by an X-Y coordinate offset. This is usually calculated forwards and backwards by independent calculations. However, a ‘B’ frame is created by taking the average macroblock created from macroblocks in frames forwards and backwards of the ‘B’ frame; i.e. 
     B 1 =I 1 −I 0 /2−I 2 /2. This is equivalent to a high pass filter: −1, 2, −1. 
     The optimum macroblocks from frames I 0  and I 2  are normally calculated independently. This is equivalent to using a filter of type: 1, −1. The filters used for MVE are not the ones used for MVC. It is possible to envisage specific patterns which could cause a serious problem with the current method of MVE. 
     It is also easy to envisage a method of MVE which overcomes the problem by comparing the I 1  frame with all combinations of vector offsets each side. However, for a vector range of +/−V pixels, the independent vector calculation is proportional to: 
     
       
         2*( V   2 ) 
       
     
     whereas, with a bidirectional search, the calculation becomes proportional to: 
     
       
         ( V   2 ) 2   =V   4 , 
       
     
     i.e. many times larger. 
     Where normal vector estimation is a severe computational problem, the prospect of bidirectional vector estimation for ‘B’ frame calculations is forbidding. No formal work has been done in this area. Indications given by the MSE values show that the normal method of MVE generation produces results which are close to the bidirectional value and it is suspected that for most pictures, there is no gain: However, designers should be aware of this problem should it ever become noticeable with certain motion sequences. If it becomes necessary to look into this area in more detail, it should be noted that there are ideas to minimise the processing impact—namely to use the independent results as a first estimate, then adopt a small search sub-area for each vector set to search for a minimum on the basis of a bi-directional search. 
     Note that the bi-directional search is only a function of encoding, and does not affect decoders; thus it is a retro-fittable feature to an encoder. 
     Almost all the results of integer motion vector estimation show a relatively slow variation of values around the minimum vector. This raises the prospect of using a filter to determine sub-pixel vectors by applying interpolation filters to the vector correlation profile rather than the signal. The concept is simply illustrated in FIG.  3 . 
     The interpolating filters should be of the half-band type defined earlier as filters  1 - 4 . It is necessary for the interpolating filter to have negative valued coefficients otherwise interpolated vector values will never be minimum. Early work in this area proved the potential of this technique, but other areas of work meant that this technique was never established over the standard method of interpolating the picture data to generate sub-pixel motion vectors. This technique still needs further work to confirm if it produces vectors which are as reliable as the conventional method. The benefit is the considerable reduction in computation time taken to produce sub-pixel vector results. 
     A significant aspect of motion vector compensation is that of applying a soft window to the macroblock structure. During tests on the 1 Mbps ‘SIF’ coded pictures, it was noticed that in areas of rapid movement, the macroblock structure becomes visible. This is clearly evident when stepping through the sequence frame by frame. The macroblock became much more visible at the low rate of 256 Kbps using ‘QIF’ pictures where the macroblocks occupy an array size of 11 by 9 and are thus 16 times the area of a ‘VID’ coded picture. 
     At such a low bit rate, it became necessary to consider methods of improving the macroblock error visibility. As mentioned earlier, using smaller sized macroblocks is not possible because of the excessive bit rate taken by larger number of vectors. However, it is possible to significantly reduce the visibility of macroblock errors by using a windowing technique. 
     The basic size of the macroblock remains 16*16 for luminance (8*8 for each chrominance); however, a window of 24*24 (12*12 for chrominance) is used for the vector assisted frame differencing. In order for the overall estimation picture to have equal gain, the edges of the window are tapered as shown in FIG. 4 which shows window functions for Y and C macroblocks. 
     The windows shown in FIG. 4 form ‘tiles’ which can be overlaid on each other to form an overall flat surface as illustrated in FIG.  5 . Using the 1-D template given in FIG.  4  and representing the window by the expression: 
     
       
         for( x= 0 ; x&lt; 24 ; x++ ) window [x]=template[x]; 
       
     
     then the 2-D window is given by the expression: 
     
       
         for( x= 0 ; x&lt; 24 ; x ++ ) 
       
     
     
       
         for( y= 0 ; y&lt; 24 ; y++ )window[x][y]=template[x]*template[y]; 
       
     
     Since the 1-D window is scaled by a value of 16, then the 2-D window is scaled by a factor of 256. 
     Tests were carried out to assess the effectiveness of windowed motion vectors used in both the motion estimation and motion compensation processes. These results are summarised in Tables 3 and 4 which show for different types of sequence, respectively: 
     (i) Using block based MVE and comparing block based MVC with window based MVC 
     (ii) Using window based MVC and comparing block based MVE with window based MVE. 
     
       
         
               
             
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 3 
               
             
             
               
                   
               
               
                 Comparing Block MVC against Windowed MVC 
               
             
          
           
               
                 MV Type: 
                 Block MVE, block MVC 
                 Block MVE, window MVC 
               
             
          
           
               
                 Sequence 
                 Q 
                 Y S/N 
                 C S/N 
                 Y bpp 
                 C bbp 
                 Σbpp 
                 Q 
                 Y S/N 
                 C S/N 
                 Y bpp 
                 C bbp 
                 Σbpp 
               
               
                   
               
             
          
           
               
                 Mobile 
                 0-8 
                 182 
                 28.35 
                 35.52 
                 .2646 
                 .1228 
                 .3260 
                 184 
                 28.42 
                 32.56 
                 .2636 
                 .1242 
                 .3257 
               
               
                 &amp; 
                  8-16 
                 175 
                 28.15 
                 32.34 
                 .2683 
                 .1140 
                 .3253 
                 177 
                 28.23 
                 32.40 
                 .2679 
                 .1150 
                 .3254 
               
               
                 Calendar 
                 16-24 
                 182 
                 28.48 
                 32.72 
                 .2681 
                 .1185 
                 .3273 
                 182 
                 28.47 
                 32.71 
                 .2656 
                 .1183 
                 .3247 
               
               
                 Renata 
                 0-8 
                 294 
                 32.88 
                 39.61 
                 .3027 
                 .0447 
                 .3250 
                 294 
                 32.90 
                 39.65 
                 .3020 
                 .0446 
                 .3243 
               
               
                   
                  8-16 
                 315 
                 33.32 
                 40.10 
                 .2984 
                 .0543 
                 .3255 
                 315 
                 33.23 
                 40.11 
                 .2999 
                 .0543 
                 .3270 
               
               
                   
                 16-24 
                 345 
                 34.00 
                 40.44 
                 .2965 
                 .0561 
                 .3245 
                 350 
                 33.96 
                 40.51 
                 .3006 
                 .0571 
                 .3291 
               
               
                 Football 
                 0-8 
                 285 
                 34.14 
                 38.60 
                 .3052 
                 .0296 
                 .3200 
                 305 
                 34.69 
                 38.90 
                 .3112 
                 .0319 
                 .3271 
               
               
                   
                  8-16 
                 285 
                 33.39 
                 38.55 
                 .3078 
                 .0251 
                 .3203 
                 300 
                 33.81 
                 38.78 
                 .3126 
                 .0263 
                 .3257 
               
               
                   
                 16-24 
                 235 
                 31.38 
                 37.33 
                 .3124 
                 .0261 
                 .3254 
                 242 
                 31.68 
                 37.45 
                 .3119 
                 .0271 
                 .3254 
               
               
                 Susie 
                 0-8 
                 940 
                 42.63 
                 47.59 
                 .2952 
                 .0643 
                 .3273 
                 920 
                 42.35 
                 47.36 
                 .2954 
                 .0617 
                 .3262 
               
               
                   
                  8-16 
                 930 
                 42.72 
                 47.54 
                 .2956 
                 .0622 
                 .3267 
                 915 
                 42.50 
                 47.44 
                 .2961 
                 .0615 
                 .3268 
               
               
                   
                 16-24 
                 860 
                 41.98 
                 47.02 
                 .2987 
                 .0548 
                 .3261 
                 860 
                 41.83 
                 47.02 
                 .2996 
                 .0548 
                 .3266 
               
               
                   
                 24-32 
                 730 
                 40.68 
                 46.39 
                 .3037 
                 .0478 
                 .3276 
                 735 
                 40.63 
                 46.53 
                 .3024 
                 .0483 
                 .3265 
               
               
                   
                 32-40 
                 470 
                 38.55 
                 43.27 
                 .3130 
                 .0288 
                 .3274 
                 494 
                 39.02 
                 43.68 
                 .3084 
                 .0306 
                 .3237 
               
               
                   
                 40-48 
                 470 
                 39.44 
                 42.36 
                 .3170 
                 .0251 
                 .3232 
                 540 
                 40.76 
                 43.03 
                 .3109 
                 .0291 
                 .3254 
               
               
                   
               
             
          
         
       
     
     
       
         
               
             
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 4 
               
             
             
               
                   
               
               
                 Comparing Block Matched MVE and Window Matched MVE 
               
             
          
           
               
                 MV Type: 
                 Block MVE, block MVC 
                 Block MVE, window MVC 
               
             
          
           
               
                 Sequence 
                 Q 
                 Y S/N 
                 C S/N 
                 Y bpp 
                 C bbp 
                 Σbpp 
                 Q 
                 Y S/N 
                 C S/N 
                 Y bpp 
                 C bbp 
                 Σbpp 
               
               
                   
               
             
          
           
               
                 Mobile 
                 0-8 
                 184 
                 28.42 
                 32.56 
                 .2636 
                 .1242 
                 .3257 
                 184 
                 28.41 
                 32.56 
                 .2646 
                 .1244 
                 .3268 
               
               
                 &amp; 
                  8-16 
                 177 
                 28.23 
                 32.40 
                 .2679 
                 .1150 
                 .3254 
                 176 
                 28.17 
                 32.36 
                 .2667 
                 .1146 
                 .3240 
               
               
                 Calendar 
                 16-24 
                 182 
                 28.47 
                 32.71 
                 .2656 
                 .1183 
                 .3247 
                 182 
                 28.48 
                 32.71 
                 .2655 
                 .1184 
                 .3247 
               
               
                 Renata 
                 0-8 
                 294 
                 32.90 
                 39.65 
                 .3020 
                 .0446 
                 .3243 
                 301 
                 33.02 
                 39.89 
                 .3041 
                 0.461 
                 .3271 
               
               
                   
                  8-16 
                 315 
                 33.23 
                 40.11 
                 .2999 
                 .0543 
                 .3270 
                 315 
                 33.27 
                 40.12 
                 .2962 
                 .0544 
                 .3234 
               
               
                   
                 16-24 
                 350 
                 33.96 
                 40.51 
                 .3006 
                 .0571 
                 .3291 
                 350 
                 34.00 
                 40.50 
                 .2988 
                 .0571 
                 .3273 
               
               
                 Football 
                 0-8 
                 305 
                 34.69 
                 38.90 
                 .3112 
                 .0319 
                 .3271 
                 308 
                 34.74 
                 39.19 
                 .3108 
                 .0324 
                 .3270 
               
               
                   
                  8-16 
                 300 
                 33.81 
                 38.78 
                 .3126 
                 .0263 
                 .3257 
                 300 
                 33.86 
                 38.91 
                 .3106 
                 .0262 
                 .3237 
               
               
                   
                 16-24 
                 242 
                 31.68 
                 37.45 
                 .3119 
                 .0271 
                 .3254 
                 242 
                 31.64 
                 37.49 
                 .3101 
                 .0271 
                 .3236 
               
               
                 Susie 
                 0-8 
                 920 
                 42.35 
                 47.36 
                 .2954 
                 .0617 
                 .3262 
                 920 
                 42.36 
                 47.35 
                 .2980 
                 .0617 
                 .3296 
               
               
                   
                  8-16 
                 915 
                 42.50 
                 47.44 
                 .2961 
                 .0615 
                 .3268 
                 930 
                 42.57 
                 47.53 
                 .2987 
                 .0622 
                 .3298 
               
               
                   
                 16-24 
                 860 
                 41.83 
                 47.02 
                 .2996 
                 .0548 
                 .3266 
                 860 
                 41.83 
                 47.01 
                 .2977 
                 .0548 
                 .3251 
               
               
                   
                 24-32 
                 735 
                 40.63 
                 46.53 
                 .3024 
                 .0483 
                 .3265 
                 738 
                 40.65 
                 46.53 
                 .3009 
                 .0485 
                 .3251 
               
               
                   
                 32-40 
                 494 
                 39.02 
                 43.68 
                 .3084 
                 .0306 
                 .3237 
                 494 
                 39.04 
                 43.69 
                 .3087 
                 .0306 
                 .3240 
               
               
                   
                 40-48 
                 540 
                 40.76 
                 43.03 
                 .3109 
                 .0291 
                 .3254 
                 540 
                 40.78 
                 43.25 
                 .3081 
                 .0293 
                 .3227 
               
               
                   
               
             
          
         
       
     
     The cost of implementing windowed MVC is relatively small and is a practical option, particularly in view of the considerable quality improvement obtained over block based MVC. This improvement is numerically most noticeable in the last two rows of the Susie results in Table 3. Other rows show little change or even slightly worse results. The visual effect of windowed MVC is, however, always better than block based MVC. 
     Turning to the results of Table 4; the results of the comparison show small differences in some sequences, but the implementation of windowed MVE is very expensive since it involves computations over a much wider area. This is reflected in the software run-time which was noticeably slower than block based MVE. This factor, together with the results of Table 5 clearly show that the effort of using both windowed MVE and windowed MVC is not worthwhile. There is also little visual improvement also. However, using block based MVE and window based MVC is very beneficial and change a previously unacceptable picture quality (the Susie sequence in particular) to a much more acceptable quality level. 
     The combination of block-based MVE and window based MVC was also applied to the SIF coded pictures at 1 Mbps with a similar quality improvement. It has yet to be established that the improvement is worthwhile at higher data rates (e.g. for ‘VID’ pictures at 4 Mbps), however, it is likely that the benefit will still exist, but at lower levels. 
     Although illustrative embodiments of the invention have been described in detail herein with reference to the accompanying drawings, it is to be understood that the invention is not limited to those precise embodiments, and that various changes and modifications can be effected therein by one skilled in the art without departing from the scope and spirit of the invention as defined by the appended claims.