Patent Document

This application is a continuation-in-part of application Ser. No. 08/815,804 filed on Mar. 12, 1997 and issued as U.S. Pat. No. 6,175,592 B1 on Jan. 16, 2001 and claims the benefit of the earlier filing date. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates to a decoder which converts and formats an encoded high resolution video signal, e.g. MPEG-2 encoded video signals, to a decoded lower resolution output video signal, and more specifically to an up-sampling filter for the decoder. 
     BACKGROUND OF THE INVENTION 
     In the United States a standard has been proposed for digitally encoded high definition television signals (HDTV). A portion of this standard is essentially the same as the MPEG-2 standard, proposed by the Moving Picture Experts Group (MPEG) of the International Organization for Standardization (ISO). The standard is described in an International Standard (IS) publication entitled, “Information Technology—Generic Coding of Moving Pictures and Associated Audio, Recommendation H.626”, ISO/IEC 13818-2, IS, 11/94 which is available from the ISO and which is hereby incorporated by reference for its teaching on the MPEG-2 digital video coding standard. 
     The MPEG-2 standard is actually several different standards. In MPEG-2, several different profiles are defined, each corresponding to a different level of complexity of the encoded image. For each profile, different levels are defined, each level corresponding to a different image resolution. One of the MPEG-2 standards, known as Main Profile, Main Level is intended for coding video signals conforming to existing television standards (i.e., NTSC and PAL). Another standard, known as Main Profile, High Level, is intended for coding high-definition television images. 
     Images encoded according to the Main Profile, High Level standard may have as many as 1,152 active lines per image frame and 1,920 pixels per line. 
     The Main Profile, Main Level standard, on the other hand, defines a maximum picture size of 720 pixels per line and 576 lines per frame. At a frame rate of 30 frames per second, signals encoded according to this standard have a data rate of 720 * 576 * 30 or 12,441,600 pixels per second. By contrast, images encoded according to the Main Profile, High Level standard have a maximum data rate of 1,152 * 1,920 * 30 or 66,355,200 pixels per second. This data rate is more than five times the data rate of image data encoded according to the Main Profile, Main Level standard. The standard proposed for HDTV encoding in the United States is a subset of this standard, having as many as 1,080 lines per frame, 1,920 pixels per line and a maximum frame rate, for this frame size, of 30 frames per second. The maximum data rate for this proposed standard is still far greater than the maximum data rate for the Main Profile, Main Level standard. 
     The MPEG-2 standard defines a complex syntax which contains a mixture of data and control information. Some of this control information is used to enable signals having several different formats to be covered by the standard. These formats define images having differing numbers of picture elements (pixels) per line, differing numbers of lines per frame or field, and differing numbers of frames or fields per second. In addition, the basic syntax of the MPEG-2 Main Profile defines the compressed MPEG-2 bit stream representing a sequence of images in five layers, the sequence layer, the group of pictures layer, the picture layer, the slice layer and the macroblock layer. Each of these layers is introduced with control information. Finally, other control information, also known as side information, (e.g. frame type, macroblock pattern, image motion vectors, coefficient zig-zag patterns and dequantization information) are interspersed throughout the coded bit stream. 
     A down conversion system converts a high definition input picture into lower resolution picture for display on a lower resolution monitor. Down conversion of high resolution Main Profile, High Level pictures to Main Profile, Main Level pictures, or other lower resolution picture formats, has gained increased importance for reducing implementation costs of HDTV. Down conversion allows replacement of expensive high definition monitors used with Main Profile, High Level encoded pictures with inexpensive existing monitors which have a lower picture resolution to support, for example, Main Profile, Main Level encoded pictures, such as NTSC or 525 progressive monitors. 
     To effectively receive the digital images, a decoder should process the video signal information rapidly. To be optimally effective, the coding systems should be relatively inexpensive and yet have sufficient power to decode these digital signals in real time. 
     One method of down conversion of the prior art simply low pass filters and decimates the decoded high resolution, Main Profile, High Level picture to form an image suitable for display on a conventional television receiver. Consequently, using existing techniques, a decoder employing down conversion may be implemented using a single processor having a complex design, considerable memory, and operating on the spatial domain image at a high data rate to perform this function. The high resolution, and high data rate, however, requires very expensive circuitry, which would be contrary to the implementation of a decoder in a consumer television receiver in which cost is a major factor. 
     SUMMARY OF THE INVENTION 
     An apparatus for forming a set of low resolution down-sampled pixel values corresponding to a current frame of a video signal from a set of low resolution pixel values corresponding to a residual image of the current frame of the video signal and from a set of down-sampled low resolution pixel values corresponding to a reference frame of the video signal. The apparatus includes a memory means for storing the set of down-sampled low resolution pixel values corresponding to the reference frame of the video signal. An up-sampling means receives from the memory means and uses Lagrangian interpolation to convert the set of down-sampled low resolution pixel values corresponding to the reference frame of the video signal into a set of up-sampled low resolution pixel values corresponding to the reference frame of the video signal. A summing means adds the set of low resolution pixel values corresponding to the residual image of the current frame of the video signal to the set of up-sampled low resolution pixel values corresponding to the reference frame of the video signal to form a set of low resolution pixel values corresponding to the current frame of the video signal. A decimating means deletes selected ones of the set of low resolution pixel values corresponding to the current frame of the video signal to generate the set of low resolution down-sampled pixel values corresponding to the current frame of the video signal. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     These and other features and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, wherein: 
     FIG. 1 is a high level block diagram of a video decoding system of the prior art; 
     FIG. 2 is a high level block diagram of an exemplary embodiment of a down conversion system; 
     FIG. 3A illustrates subpixel positions and corresponding predicted pixels for exemplary embodiments of 3:1 and 2:1 down conversion systems; 
     FIG. 3B shows the up-sampling process which is performed for each row of an input macroblock for an exemplary down conversion system; 
     FIG. 4 shows the frequency characteristics of three different up-sampling filters; 
     FIGS. 5A-5C show the interpolation of a rectangular pulse using three different up-sampling filters; 
     FIGS. 6A-6F show the interpolation of a moving rectangular pulse at predicted frame numbers  1 ,  2 ,  3 ,  5 ,  8 , and  10 , when using an equi-ripple up-sampling filter; 
     FIG. 7 shows the interpolation of a moving rectangular pulse at predicted frame number  10  when using a Lagrangian up-sampling filter; 
     FIG. 8 shows the interpolation of a moving rectangular pulse at predicted frame number  10  when using a Bi-linear up-sampling filter; 
     FIG. 9 illustrates the multiplication pairs for the first and second output pixel values of an exemplary embodiment of a block mirror filter; 
     FIG. 10A shows input and decimated output pixels for 4:2:0 video signal using 3:1 decimation; and 
     FIG. 10B shows input and decimated output pixels for 4:2:0 video signal using 2:1 decimation. 
    
    
     DETAILED DESCRIPTION 
     I. DECODER OVERVIEW 
     The exemplary embodiment of the invention filters decoded HDTV signals which have been encoded according to the MPEG-2 standard and in particular, the Main Profile, High Level MPEG-2 standard. 
     The invention described herein, however, is not limited to down conversion filtering of decoded HDTV signals. The filtering method described below may also be used to filter other types of frequency-domain encoded digital signals which may be divided into sections, filtered, and then recombined. 
     The MPEG-2 Main Profile standard defines a sequence of images in five levels: the sequence level, the group of pictures level, the picture level, the slice level and the macroblock level. Each of these levels may be considered to be a record in a data stream, with the later-listed levels occurring as nested sub-levels in the earlier listed levels. The records for each level include a header section which contains data that is used in decoding its sub-records. 
     Macroblocks are composed of six blocks, 4 luminance blocks Y and 2 chrominance blocks, Cr and Cb. Each block of the encoded HDTV signal contains data representing 64 respective coefficient values of a two dimensional discrete cosine transform (DCT) representation of 64 picture elements (pixels) in the HDTV image. 
     In the encoding process, the pixel data is subject to motion compensated differential coding prior to the discrete cosine transformation and the blocks of transformed coefficients are further encoded by applying run-length and variable length encoding techniques. A decoder which recovers the image sequence from the data stream reverses the encoding process. This decoder employs an entropy decoder (e.g. a variable length decoder), an inverse discrete cosine transform processor, a motion compensation processor, and an interpolation filter. 
     FIG. 1 is a high level block diagram of a typical video decoding system of the prior art. The video decoder of the prior art includes an entropy decoder  110 , which is usually a variable length decoder and a run length decoder, an inverse quantizer  120 , and an inverse discrete cosine transform (IDCT) processor  130 . The exemplary system also includes a controller  170  which controls the various components of the decoding system responsive to the control information retrieved from the input bit stream by the entropy decoder  110 . For processing of prediction images, the prior art system further includes a memory  160 , adder  140 , a motion compensation processor  150 , and a block to raster converter  180 . 
     The variable length decoder  110  receives the encoded video image signal, and reverses the encoding process to produce control information including motion vectors describing the relative displacement of a matching macroblock in a previously decoded image. This matching macroblock corresponds to a macroblock of the predicted picture that is currently being decoded. The variable length decoder  110  also receives the quantized DCT transform coefficients of the blocks of either the current video image, if intraframe encoding is used, or the difference between the current and the predicted video image which is referred to as the residual image, if interframe encoding is used. The inverse quantizer  120  receives the quantized DCT transform coefficients and reconstructs the quantized DCT coefficients for a particular macroblock. The quatization matrix to be used for a particular block is received from the variable length decoder  110 . 
     The IDCT processor  130  transforms the reconstructed DCT coefficients to pixel values in the spatial domain (for each block of 8×8 matrix values representing luminance or chrominance components of the macroblock, and for each block of 8×8 matrix values representing the differential luminance or differential chrominance components of the predicted macroblock). 
     If the current macroblock is not predictively encoded, then the output matrix values are the pixel values of the corresponding macroblock of the current video image. If the macroblock is interframe encoded, the corresponding macroblock of the previous video picture frame (a reference frame) is stored in memory  160  for use by the motion compensation processor  150 . The motion compensation processor  150  receives the previous macroblock from memory  160  responsive to the motion vector which is received from the entropy decoder  110 . The motion compensation processor  150  then adds the previous macroblock to the current IDCT transformed macroblock (corresponding to a residual component of the present predictively encoded frame) in adder  140  to produce the corresponding macroblock of pixels for the current video image, which is then stored into the memory  160 . 
     II. DOWN CONVERSION SYSTEM 
     A. Overview 
     FIG. 2 is a high level block diagram of an exemplary embodiment of a down conversion system. As shown in FIG. 2, the down conversion system includes a variable length decoder (VLD)  210 , a run-length (R/L) decoder  212 , an inverse quantizer  214 , and an inverse discrete cosine transform (IDCT) processor  218 . In addition, the down conversion system includes a down conversion filter (DCT filter)  216  and down sampling processor  232  for filtering of encoded pictures. While the following describes the exemplary embodiment for a Main Profile, High Level encoded input, the down conversion system may be implemented with any similarly encoded high resolution image bit stream. 
     The down conversion system also includes a motion vector (MV) translator  220 , a high resolution motion block generator  224  including up-sampling processor  226  and half-pixel generator  228  and a reference frame memory  222 . 
     In addition, the system includes a display conversion block  280  including a vertical programmable filter (VPF)  282  and horizontal programmable filter (HZPF)  284 . The display conversion block  280  converts downsampled images into images for display on a particular display having a lower resolution. 
     The down conversion filter  216  performs a lowpass filtering of the high resolution (e.g. Main Profile, High Level DCT) coefficients in the frequency domain. The down sampling processor  232  eliminates spatial pixel values by decimation of the lowpass filtered Main Profile, High Level picture to produce a set of pixel values which can be displayed on a monitor having lower resolution than that required to display a Main Profile, High Level picture. The exemplary reference frame memory  222  stores the spatial pixel values corresponding to at least one previously decoded reference frame having a resolution corresponding to the down-sampled picture. For non-intra macroblock encoding, the MV translator  220  scales the motion vectors for each block of the received picture consistent with the reduction in resolution, and the low resolution motion block generator  224  receives the decimated low resolution motion blocks provided by the reference frame memory  222 , up-samples these motion blocks and generates half pixel values to provide motion blocks at the half pixel accuracy which exhibit good spatial correspondence to the decoded and filtered differential pixel blocks. 
     The operation of this exemplary embodiment of a down conversion system for intra-macroblock encoding is now described. The Main Profile, High Level bit-stream is received and decoded by VLD  210 . In addition to header information used by the HDTV system, the VLD  210  provides DCT coefficients for each block and macroblock, and motion vector information. The DCT coefficients are run length decoded in the R/L decoder  212  and inverse quantized by the inverse quantizer  214 . The VLD  210  and R/L decoder  212  correspond to the entropy decoder  110  of FIG.  1 . 
     Since the received video image represented by the DCT coefficients is a high resolution picture, the DCT coefficients of each block are lowpass filtered before decimation of the high resolution video image. The inverse quantizer  214  provides the DCT coefficients to the DCT filter  216  which performs a lowpass filtering in the frequency domain by weighting the DCT coefficients with predetermined filter coefficient values before providing them to the IDCT processor  218 . In an exemplary embodiment, this filter operation is performed on a block by block basis. 
     The IDCT processor  218  provides spatial pixel values by performing an inverse discrete cosine transform of the filtered DCT coefficients. The down sampling processor  232  reduces the picture sample size by eliminating spatial pixel sample values according to a predetermined decimation ratio; therefore, storing the lower resolution picture uses a smaller frame memory  222  compared to that which would be needed to store the higher resolution Main Profile, High Level picture. 
     The operation of this exemplary embodiment of a down conversion system for non-intra macroblock encoding is now described. In this exemplary embodiment, following the MPEG standard, the DCT coefficients of the current received image represent the DCT coefficients of the residual components of the predicted image macroblocks. The predicted image macroblocks can be forward, backward, and bi-directionally predicted. In a bi-directional case, for example, a forward predicted image macroblock and a backward predicted image macroblock may be averaged to provide the bi-directionally predicted image macroblock. The horizontal components of the motion vectors for a predicted frame are scaled since the down sampled low resolution reference pictures of previous frames stored in memory do not have the same number of pixels as the high resolution predicted frame (Main Profile, High Level). 
     Referring to FIG. 2, the motion vectors of the Main Profile, High Level bit stream provided by the VLD  210  are provided to the MV translator  220 . Each motion vector is scaled by the MV translator  220  to reference the appropriate prediction block of the reference frame of a previous image stored in reference frame memory  222 . The size (number of pixel values) in the retrieved block is smaller than a block of the corresponding high resolution block used to encode the current image; consequently, the retrieved block is up-sampled to form a prediction block having the same number of pixels as the residual block provided by the IDCT processor  218 . 
     The forward or backward prediction block is up-sampled by the up-sampling processor  226  responsive to a control signal from the MV translator  220  to generate a block corresponding to the original high resolution block of pixels. Then, half pixel values are generated, if indicated by the motion vector for the up-sampled prediction block in the half-pixel generator  228 , to ensure proper spatial alignment of the prediction block. In the bi-directional case, for example, the forward and backward predicted image macroblocks of upsampled pixels may be averaged to provide a bi-directionally predicted image macroblock. The up-sampled and aligned prediction block is added in adder  230  to the current filtered block, which is, for this example, the reduced resolution residual component from the predicted block. All the processing is done on a macroblock by macroblock basis. After the motion compensation process is complete for the current macroblock in the upsampling domain, the reconstructed macroblock is decimated accordingly in the down sampling processor  232 . This process does not reduce the resolution of the image but simply removes redundant pixels from the low resolution filtered image. 
     Once the downsampled macroblocks for an image are available, the display conversion block  280  adjusts the image for display on a low resolution television display by filtering the vertical and horizontal components of the downsampled image in the VPF  282  and the HZPF  284  respectively. 
     B. Macroblock Prediction 
     Since the reference frames of previous images are down sized, the received motion vectors pointing to these frames may also be translated according to the conversion ratio. The following describes the motion translation for the luminance block, for example, in the horizontal direction. One skilled in the art would easily extend the following discussion to motion translation in the vertical direction if used. Denoting x and y as the current macroblock address in the original image frame, Dx as the horizontal decimation factor and mv x  as the half pixel horizontal motion vector of the original image frame, the address of the top left pixel of the motion block in the original image frame, denoted as XH in the half pixel unit, is given by (1): 
     
       
         XH=2x+mv x   (1)  
       
     
     The pixel corresponding to the motion block starts in the down-sampled image, whose address is denoted as x* and y* in the pixel unit given in (2).                  x   *     =     XH     2   ·   Dx         ;       y   *     =   y             (   2   )                                
     Because the exemplary DCT filter  216  and down sampling processor  232  only reduce the horizontal components of the image, the vertical component of the motion vector is not affected. For the chrominance, the motion vector is a half of a luminance motion vector in the original picture. Therefore, definitions for translating the chrominance motion vector may also use the two equations (1) and (2). 
     Motion prediction is done by a two step process: first, pixel accuracy motion estimation in the original image frame restored by up-sampling the down-sampled image frame in the up-sampling processor  226  of FIG. 2, then the half-pixel generator  228  performs a half pixel motion estimation by averaging of nearest pixel values. 
     Subpixels in a decimated picture, which correspond to pixels in an original pixture, are interpolated, for example, using an up-sampling polyphase filter in the up-sampling processor  226 , which gives a motion prediction in the original picture. The motion prediction is added in adder  230  to an output of the IDCT processor  218 . Since the output values of the adder  230  correspond to an image in the upsampled original picture format, these values may be downsampled for display on a display having a lower resolution. Downsampling in the down sampling processor  232  is substantially equivalent to subsampling of an image frame, but adjustments may be made based upon the conversion ratio. For example, in the case of 3:1 downsampling, the number of horizontally downsampled pixels are 6 or 5 for each input macroblock, and the first downsampled pixels are not always the first pixel in the input macroblock. 
     After acquiring the correct motion prediction block from the down-sampled image, up-sampling is needed to get the corresponding prediction block in the original picture. Consequently, subpixel accuracy in motion block prediction is desirable in the down sampled picture. For example, using  3 : 1  decimation, it is desirable to have ⅓(or ⅙) subpixel accuracy in the motion prediction. The subpixel which is a first pixel required by the motion vector, in addition to the down-sampled motion block, is determined. Then, subsequent subpixel positions are determined using modulo arithmetic as described in the following. The subpixel positions are denoted as x s  as given in (3):                X   s     =       (     XH   2     )        %        (   Dx   )               (   3   )                                
     where “%” represents modulo division. 
     For example, the ranges of x s  are 0, 1, 2 for 3:1 up-sampling and 0, 1 for 2:1 up-sampling. FIG. 3A shows subpixel positions and corresponding 17 predicted pixels for the 3:1 and 2:1 examples, and Table 1 gives the legend for FIG.  3 A. 
     
       
         
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                 Symbol 
                 Pixel 
               
               
                   
               
             
             
               
                 * 
                 Downsampled Pixel 
               
               
                 Δ 
                 Upsampled Pixel 
               
               
                 ◯ 
                 Prediction Pixel 
               
               
                   
                 Extra Right and Left 
               
               
                   
                 Pixels for Upsampling 
               
               
                   
               
             
          
         
       
     
     As previously described, the up-sampling filters may be up-sampling polyphase filters, and Table 2A gives characteristics of these up-sampling polyphase interpolation filters. 
     
       
         
               
               
               
             
               
               
               
             
           
               
                   
                 TABLE 2A 
               
               
                   
                   
               
               
                   
                 3:1 
                 2:1 
               
               
                   
                 Upsampling 
                 Upsampling 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                 Number of Polyphase Filters 
                 3 
                 2 
               
               
                 Number of Taps 
                 3 
                 5 
               
               
                 Maximum number of horizontal 
                 9 
                 13 
               
               
                 downsampled pixels 
               
               
                   
               
             
          
         
       
     
     Tables 2B and 2C below, show exemplary polyphase filter coefficients for the exemplary 3:1 and 2:1 up-sampling polyphase equi-ripple filters. 
     
       
         
               
             
               
               
               
               
             
               
               
               
               
             
           
               
                 TABLE 2B 
               
             
             
               
                   
               
               
                 3:1 Up-sampling Filter 
               
             
          
           
               
                   
                 Phase 0 
                 Phase 1 
                 Phase 2 
               
               
                   
                   
               
             
          
           
               
                 Double Precision 
                 −0.1638231735591 
                 0.0221080691070 
                  0.3737642376078 
               
               
                   
                  0.7900589359512 
                 0.9557838617858 
                  0.7900589359512 
               
               
                   
                  0.3737642376078 
                 0.0221080691070 
                 −0.1638231735591 
               
               
                 Fixed Point (9 bits) 
                 −0.1640625 (−42) 
                 0.0234375 (6) 
                  0.3750000 (96) 
               
               
                   
                  0.7890625 (202) 
                 0.95703125 (244) 
                  0.7890625 (202) 
               
               
                   
                  0.3750000 (96) 
                 0.0234375 (6) 
                 −0.1640625 (−42) 
               
               
                   
               
             
          
         
       
     
     
       
         
               
             
               
               
               
             
               
               
               
               
             
           
               
                 TABLE 2C 
               
             
             
               
                   
               
               
                 2:1 Up-sampling Filter 
               
             
          
           
               
                   
                 Phase 0 
                 Phase 1 
               
               
                   
                   
               
             
          
           
               
                   
                 Double 
                 0.0110396839260 
                 −0.1433363887113 
               
               
                   
                 Precision 
                 0.0283886402920 
                  0.6433363887113 
               
               
                   
                   
                 0.9211433515636 
                  0.6433363887113 
               
               
                   
                   
                 0.0283886402920 
                 −0.1433363887113 
               
               
                   
                   
                 0.0110396839260 
                  0.0000000000000 
               
               
                   
                 Fixed Point 
                 0.01718750 (3) 
                 −0.14453125 (−37) 
               
               
                   
                 (9 bits) 
                 0.02734375 (7) 
                  0.64453125 (165) 
               
               
                   
                   
                 0.92187500 (236) 
                  0.64453125 (165) 
               
               
                   
                   
                 0.02734375 (7) 
                 −0.14453125 (−37) 
               
               
                   
                   
                 0.01718750 (3) 
                  0.00000000 (0) 
               
               
                   
                   
               
             
          
         
       
     
     Although the exemplary coefficients in Tables 2B and 2C are given for equi-ripple filters, other filters may be used for interpolating decimated pixels. For example, in section II.C., the design considerations regarding choosing an appropriate upsampling filter are disclosed. In particular, section II.C. discloses a comparison of motion tracking characteristics between equi-ripple, bi-linear, and Lagrangian upsampling filters. 
     In a fixed point representation, the numbers in parenthesis of Table 2B and Table 2C are 2&#39;s complement representations in 9 bits with the corresponding double precision numbers on the left. Depending upon the subpixel position of the motion prediction block in the downsampled reference image frame, one corresponding phase of the polyphase interpolation filter is used. Also, in an exemplary embodiment, more pixels on the left and right are needed to interpolate 17 horizontal pixels in the downsampled image frame. For example, in the case of 3:1 decimation, there are a maximum of 6 horizontally downsampled pixels for each input macroblock. However, when up-sampling, 9 horizontal pixels are needed to produce the corresponding motion prediction block values because an up-sampling filter requires more left and right pixels outside of the boundary for the filter to operate. Since the exemplary embodiment employs half pixel motion estimation, 17 pixels are needed to get 16 half pixels which can be either the first 16 integer pixels or the average values of nearest two pixel samples. A half pixel motion generator takes care of this. Table 3 illustrates mapping between subpixel positions and polyphase filter elements, and a number of left pixels which are needed in addition for the up-sampling process. 
     
       
         
               
               
               
               
               
             
               
               
               
               
               
             
           
               
                   
                 TABLE 3 
               
               
                   
                   
               
               
                   
                 Sub Pixel 
                   
                 No. of Extra 
                 Coordinate 
               
               
                   
                 Position 
                 Polyphase 
                 Left Pixels 
                 Change 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                 3:1 Upsampling 
                 0 
                 1 
                 1 
                 x − &gt; x − 1 
               
               
                   
                 1 
                 2 
                 1 
                 x − &gt; x − 1 
               
               
                   
                 2 
                 0 
                 0 
               
               
                 2:1 Upsampling 
                 0 
                 0 
                 2 
                 x − &gt; x − 2 
               
               
                   
                 1 
                 1 
                 2 
                 x − &gt; x − 2 
               
               
                   
               
             
          
         
       
     
     FIG. 3B summarizes the up-sampling process which is performed for each row of an input macroblock. First, in step  310 , the motion vector for the block of the input image frame being processed is received. At step  312 , the motion vector is translated to correspond to the downsampled reference frame in memory. At step  314 , the scaled motion vector is used to retrieve the coordinates of the prediction block stored in frame memory. At step  316  the subpixel point for the block is determined and the initial polyphase filter values for up-sampling are then retrieved at step  318 . The identified pixels for the prediction block of the stored downsampled reference frame are then retrieved from memory at step  320 . 
     Before the first pass at the filtering step  324 , the registers are initialized at step  322 , which for the exemplary embodiment entails loading the registers with the initial 3 or 5 pixel values. Then, after filtering step  324 , the process determines at step  326  whether all pixels have been processed. In the exemplary embodiment 17 pixels are processed. If all pixels have been processed, the up-sampled block is complete. If all pixels have not been processed, the phase is updated at step  328 , and the phase is checked, for the 0 value. If the phase is not zero, the registers must be updated for the next set of polyphase filter coefficients. Updating registers step  332  then simply updates the input pixels. In an exceptional case where the left-most pixel is outside of the block boundary, a previous pixel value may be repeated. 
     C. Upsampling for Good Motion Tracking 
     With reference to FIG. 2, described above in Section II.B., the up-sampling processor  226  retrieves a block of down sampled pixels from the reference frame memory  222 . The up-sampling processor  226  then uses interpolation to generate pixels to provide a prediction block. This results in a prediction block with the same number of pixels as the reduced resolution residual block to which it is added in the adder  230 . 
     The output of the adder  230  is then down sampled by the down sampling processor  232 , stored in the reference frame memory  222 , and then up sampled by the up-sampling processor  226  to generating the next prediction block. This cycle is repeated for each predicted frame, both P-frames and B-frames. 
     Since most coding schemes use multiple predicted frames between intra-coded frames, if image distortion is introduced by the up-sampling processor  226 , this image distortion is also cycled through this process. The image distortion may be accumulated by the up-sampling processor  226  during each cycle. If many consecutive predicted frames are coded between intra-coded frames, this distortion may be amplified to the point where it becomes visible. 
     A source of such image distortion may be poor motion tracking characteristics of the up-sampling processor  226 . Preferably, an up sampling filter in a down conversion system has both smooth low pass filtering and good motion tracking characteristics. Depending on the particular coding structure and the number of forward predicted frames between intra-coded frames, in some applications, the motion tracking property may take precedence over the low pass filtering to prevent visible motion jerkiness in a reproduced image. 
     FIG. 4 shows the frequency response (dB vs. frequency, where π corresponds to half of the sampling frequency) of three different upsampling filters in a 3:1 horizontal down conversion system: an equi-ripple filter frequency response  410 , a bi-linear filter frequency response  430 , and a Lagrangian filter frequency response  420 . The cutoff frequency  440  is equal to π/3 for the 3:1 decimation system (π/2 for a 2:1 decimation system). 
     The following example illustrates the motion tracking properties of these filters in a 3:1 down conversion system. These examples concern an image of a rectangular pulse moving one pixel per frame in the upsample domain. For the purposes of this example, the coding structure consists of all forward predicted frames after an intra-frame. The image is interpolated based on every third pixel since the other pixels were thrown out during down sampling. 
     FIGS. 5A,  5 B, and  5 C, show the interpolations  520 ,  530 ,  540  of the rectangular pulse by an equi-ripple filter, a bi-linear filter,, and a third order, Lagrangian filter, respectively. The dashed lines  510  (not visible in FIG. 5B) represent the rectangular pulse being interpolated. Lagrangian interpolation is well known to those skilled in the art and is taught by Atkinson,  An Introduction to Numerical Analysis,  107-10 (1978), which is incorporated hereinby reference. As shown in FIGS. 5A-5C, the equi-ripple filter interpolation  520  has the most overshoot and undershoot in comparison to the Lagrangian filter interpolation  540  and the bi-linear filter interpolation  530 . 
     FIGS. 6A,  6 B,  6 C,  6 D,  6 E, and  6 F illustrate equi-ripple filter interpolations of the moving (one pixel per frame) rectangular pulse in predicted frame numbers  1 ,  2 ,  3 ,  5 ,  8  and  10 , respectively. The dashed lines  610  in FIGS. 6A-6F represent the original image. The solid lines  620  in FIGS. 6A-6F represent the equi-ripple interpolations of the downsampled original image  610 . In frame number  5  shown in FIG. 6D, the interpolated pulse  620  is distorted and has moved ahead of the original pulse  610 . In frame number  10  shown in FIG. 6F, the interpolated pulse  620  is even further ahead of the original pulse  610  than in frame number  5  shown in FIG.  6 D. 
     When the next intra-coded frame is displayed, the difference between the interpolated pulse  620  in FIG.  6 F and the original pulse  610  will result in a “snapping back” problem. This is caused when the interpolated image in the predicted frames moves ahead of the motion of the original image and is then followed by an accurately represented intra-coded frame. Since the motion of edges in predicted frames are ahead of the motion of the original image, the next intra-coded frame may give a viewer the impression that the motion is now going backward. 
     For example, when the original image is an image of a person turning his head slowly to the left, the “snapping back” problem may result in the person&#39;s head “snapping back” to the right at every intra-coded frame when an equi-ripple filter of the above example is used for up-sampling. The severity of this type of distortion depends on the actual coding structure. For example, when applied to an IBBP coding structure, which has two Bi-directional frames between reference frames, the artifact is less noticable than in the example provided with reference to FIGS. 6A-6F where there were 10 consecutive forward predicted frames. 
     FIGS. 7 and 8 show images interpolated using Lagrangian and Bi-linear interpolators, respectively, for predicted frame number  10  under the same conditions as in FIG. 6F for an equi-ripple interpolator. In comparison to the equi-ripple interpolation  620  of FIG. 6F, the Lagrangian interpolation  720  in FIG.  7  and the Bi-linear interpolation  820  in FIG. 8 provide better motion tracking since their interpolated pulses  720 ,  820  are comparatively less ahead of the original image  610 . 
     Overshoot and undershoot are factors to consider when analyzing the predicted pulse distortion. The equi-ripple interpolation  620  of FIG. 6F has 16% over/undershoot, the third order Lagrangian interpolation  720  of FIG. 7 has 6% over/undershoot, and the bi-linear interpolation  820  of FIG. 8 has no over/undershoot. 
     Comparison of FIGS. 6F,  7 , and  8 , shows that both a Lagrangian filter and a bi-linear filter provide better motion tracking characteristics than an equi-ripple filter. In an exemplary embodiment of the present invention, a bi-linear filter or a Lagrangian filter is used in up-sampling processor  226 . 
     In another exemplary embodiment of the present invention, a Lagrangian filter is used in up-sampling processor  226 . The third order Lagrangian filter has a better frequency response compared to a bilinear filter (as shown in FIG. 4) and has less over/undershoot than an equi-ripple filter (as shown by comparing FIGS.  6 F and  7 ). 
     It is shown that a bilinear filter is the same as a first order Lagrangian filter. As known to those skilled in the art of numerical analysis, a Lagrangian interpolator, which is a polynomial interpolation for giving data points, may be designed as follows. 
     For giving (n+1) discrete data points, the n-th order Lagrangian interpolator is in the form of:            P   n          (   x   )       =       ∑     i   =   0     n            y   i     ·       l   i          (   x   )                                  
     where y i  is a function value at x i  and l i (x) is a n-th order polynomial and is in the form of:            l   i          (   x   )       =       ∏     n   ≠   i              (     x   -     x   n       )       (       x   i     -     x   n       )                                
     From the above equations it is evident that l i (x n )=1 for n=i and l i (x n )=0 for n≠i. Therefore, P n (X n )=Y n  and the interpolation polynomial satisfies (n+1) discrete data points. 
     The first order Lagrangian interpolator is:            P   1          (   x   )       =           (     x   -     x   1       )       (       x   0     -     x   1       )       ·     y   0       +         (     x   -     x   0       )       (       x   1     -     x   0       )       ·     y   1                                
     where x O &lt;x&lt;x 1 . 
     It is self-evident that the first order Lagrangian interpolator is a bilinear. The second order Lagrangian interpolator P 2 (x) and the third order Lagrangian interpolator P 3 (x) shown below may be derived from the above equations.            P   2          (   x   )       =             (     x   -     x   1       )     ·     (     x   -     x   2       )           (       x   0     -     x   1       )     ·     (       x   0     -     x   2       )         ·     y   0       +           (     x   -     x   0       )     ·     (     x   -     x   2       )           (       x   1     -     x   0       )     ·     (       x   1     -     x   2       )         ·     y   1       +           (     x   -     x   0       )     ·     (     x   -     x   1       )           (       x   2     -     x   0       )     ·     (       x   2     -     x   1       )         ·     y   2                     P   3          (   x   )       =             (     x   -     x   1       )     ·     (     x   -     x   2       )     ·     (     x   -     x   3       )           (       x   0     -     x   1       )     ·     (       x   0     -     x   2       )     ·     (       x   0     -     x   3       )         ·     y   0       +           (     x   -     x   0       )     ·     (     x   -     x   2       )     ·     (     x   -     x   3       )           (       x   1     -     x   0       )     ·     (       x   1     -     x   2       )     ·     (       x   1     -     x   3       )         ·     y   1       +           (     x   -     x   0       )     ·     (     x   -     x   1       )     ·     (     x   -     x   3       )           (       x   2     -     x   0       )     ·     (       x   2     -     x   1       )     ·     (       x   2     -     x   3       )         ·     y   2       +           (     x   -     x   0       )     ·     (     x   -     x   1       )     ·     (     x   -     x   2       )           (       x   3     -     x   0       )     ·     (       x   3     -     x   1       )     ·     (       x   3     -     x   2       )         ·     y   3                                
     For 2:1 upsampling, we are interested in interpolating points that are at half pixel locations between pixels in the decimated image. For 3:1 upsampling, we are interested in interpolating points that are at one-third or two-third pixel locations between pixels in the decimated image. For example, for a half pixel in the 2:1 upsampling case, x-x 0 =½, x-x 1 −½ and x 1 -x 0 =1. By substituting these values, filter coefficients can be derived. 
     Table 7, below, shows the Lagrangian filter coefficients for a 2:1 up-sampling filter. 
     
       
         
               
               
               
               
             
           
               
                   
                 TABLE 7 
               
               
                   
                   
               
               
                   
                 Order of 
                   
                   
               
               
                   
                 Filter 
                 PHASE 0 
                 PHASE 1 
               
               
                   
                   
               
             
             
               
                   
                 First 
                 (1,0) 
                 (1/2,1/2) 
               
               
                   
                 Second 
                 (0,1,0) 
                 (−1,6,3)/8 
               
               
                   
                 Third 
                 (0,1,0,0) 
                 (−1,9,9,−1)/16 
               
               
                   
                 Fourth 
                 (0,0,1,0,0) 
                 (3,−20,90,60,−5)/128 
               
               
                   
                   
               
             
          
         
       
     
     Table 8, below, shows the Lagrangian filter coefficients for a 3:1 up-sampling filter. 
     
       
         
               
               
               
               
               
             
           
               
                 TABLE 8 
               
               
                   
               
               
                 Order 
                   
                   
                   
                 Input 
               
               
                 of Filter 
                 PHASE 0 
                 PHASE 1 
                 PHASE 2 
                 Shift 
               
               
                   
               
             
             
               
                 First 
                 (1,0) 
                 (2/3,1/3) 
                 (1/3,2/3) 
                 Phase 0 
               
               
                 Second 
                 (0,1,0) 
                 (−1/9,8/9,2/9) 
                 (2/9,8/9,−1/9) 
                 Phase 2 
               
               
                 Third 
                 (0,1,0,0) 
                 (−5,60,30,−4)/81 
                 (−4,30,60,−5)/81 
                 Phase 0 
               
               
                 Fourth 
                 (0,0,1,0,0) 
                 (5,−35,210,70,−7)/ 
                 (−7,70,210,−35,5)/ 
                 Phase 2 
               
               
                   
                   
                 243 
                 243 
               
               
                   
               
             
          
         
       
     
     In Tables 7 and 8, phase  0  means integer pixel, phase  1  means a half pixel in the 2:1 case and one third point between pixels in the 3:1 case, and phase  2  means two third point between pixels in the 3:1 case. In the 2:1 case, input pixels are shifted for filtering at phase  0 , but in the 3:1 case input shifting does not always occur at phase  0 . 
     As known to those skilled in the art, as the order of a filter increases, the frequency response of the filter improves. Although many filter design methods are based strictly on improving the frequency response of a filter, in a down conversion system, the spatial response of the filter, which corresponds to its motion tracking characteristics, is an additional design consideration. Table 9 below shows the percentage over/under shoot for different order Lagrangian polyphase filters for a 3:1 down conversion system. 
     
       
         
               
               
               
             
           
               
                   
                 TABLE 9 
               
               
                   
                   
               
               
                   
                 Order 
                 Percentage Over/Undershoot 
               
               
                   
                   
               
             
             
               
                   
                 2 nd   
                 11% 
               
               
                   
                 3 rd   
                  6% 
               
               
                   
                 4 th   
                   12.5% 
               
               
                   
                   
               
             
          
         
       
     
     Human eyes are very sensitive to edge movement as long as it is traceable. The overshoot and undershoot of an upsampling filter deteriorates upsampling of a macroblock as more successive predicted frames are decoded and the results of previous upsample operations are recycled through the upsample filter. An upsampling filter design should be optimized to provide sufficient motion tracking characteristics while at the same time providing low pass filtering. In an exemplary embodiment of a 3:1 down conversion system, the up-sampling processor  226  uses the third order Lagrangian filter for interpolation of a down-sampled image. This results in a balance between the motion tracking characteristics and the low pass filtering response. The 4 th  order filter may have a better frequency response than the 3 rd  order filter but the 3 rd  order filter has better motion tracking characteristics. Thus this particular design balances these factors and makes a tradeoff between them. As discussed above, the coding structure of a particular system determines where this balance should fall. 
     D. DCT Domain Filtering Employing Weighting of DCT Coefficients 
     The exemplary embodiment of the down conversion system includes the DCT filter  216  processing the DCT coefficients in the frequency domain, which replaces a lowpass filter in the spatial domain. There are several advantages in DCT domain filtering instead of spatial domain filtering for DCT coded pictures, such as contemplated by the MPEG or JPEG standards. Most notably, a DCT domain filter is computationally more efficient and requires less hardware than a spatial domain filter applied to the spatial pixels. For example, a spatial filter having N taps may use as many as N multiplications and additions for each spatial pixel sample value. This compares to only one multiplication in the DCT domain filter. 
     The simplest DCT domain filter is a truncation of the high frequency DCT coefficients. However, truncation of high frequency DCT coefficients does not result in a smooth filter and has drawbacks such as “ringing” near edges in the decoded picture. The DCT domain lowpass filter of the exemplary embodiment of the invention is derived from a block mirror filter in the spatial domain. The filter coefficient values for the block mirror filter are, for example, optimized in the spatial domain, and these values are then converted into coefficients of the DCT domain filter. 
     Although the exemplary embodiment shows DCT domain filtering in only the horizontal direction, DCT domain filtering can be done in either the horizontal or the vertical direction or both by combining horizontal and vertical filters. 
     E. DCT Domain Filter Coefficients 
     One exemplary filter of the present invention is derived from two constraints: first, the filter processes image data on a block by block basis for each block of the image without using information from other blocks of the same picture or from previous pictures; and second, the filter reduces visibility of block boundaries which occur when the filter processes boundary pixel values. 
     According to the first constraint, in the DCT based compression of an MPEG image sequence, for example, blocks of N X N DCT coefficients yield blocks of N X N spatial pixel values. Consequently, an exemplary embodiment of the present invention implements a DCT domain filter which only processes blocks of the currently received picture. 
     According to the second constraint, if the filter is simply applied to a block of spatial pixel values, there is a transition of filtering on the block boundary which is caused by an insufficient number spatial pixel values beyond the boundary to fill the residual of the filter. That is to say, the edge of a block cannot be properly filtered because the N-tap filter has respective input pixels for only N/2 or for (N/2)-1 taps depending upon whether N is even or odd. The remaining input pixels are beyond the boundary of the block. Several methods of supplying pixel values exist: 1) repeat a predetermined constant pixel value beyond a boundary; 2) repeat the same pixel value as the boundary pixel value; and 3) mirror the pixel values of the block to form previous and subsequent blocks of pixel values adjacent to the processed block. Without prior information on the contents of the previous or subsequent block, the mirroring method is considered as a preferred method. Therefore, an embodiment of the present invention employs this mirroring method for the filter and is termed a “block mirror filter.” 
     The following describes an exemplary embodiment which implements a horizontal block mirror filter that lowpass filters  8  input spatial pixel sample values of a block. If the size of the input block is an 8×8 block matrix of pixel sample values, then a horizontal filtering can be done by applying the block mirror filter to each row of 8 pixel sample values. It will be apparent to one skilled in the art that the filtering process can be implemented by applying the filter coefficients columnwise of the block matrix, or that multidimensional filtering may be accomplished by filtering of the rows and then filtering the columns of the block matrix. 
     A block mirror filter in the spatial domain can be equivalently implemented in the DCT domain by weighting DCT coefficients, as taught by Kim et. al., “DCT Domain Filter for ATV Down Conversion”, IEEE Trans. on Consumer Electronics, Vol. 43 (4) 1074-8 (1997). FIG. 4 shows the correspondence between the input pixel values x 0  through X 7  (group XO) for an exemplary mirror filter for 8 input pixels which employs a 15 tap spatial filter represented by tap values h 0  through h 14 . The input pixels are mirrored on the left side of group X0, shown as group X1, and on the right side of group X0, shown as group X2. The output pixel value of the filter is the sum of 15 multiplications of the filter tap values with the corresponding pixel sample values. FIG. 4 illustrates the multiplication pairs for the first and second output pixel values. 
     F. Exemplary Embodiment of the Block Mirror Filter 
     One embodiment of the exemplary block mirror filtering of the present invention is derived as by the following steps: 1) a one dimensional lowpass symmetric filter is chosen with an odd number of taps, which is less than 2N taps; 2) the filter coefficients are increased to 2N values by padding with zero&#39;s; 3) the filter coefficients are rearranged so that the original middle coefficient goes to the zeroth position by a left circular shift; 4) the DFT coefficients of the rearranged filter coefficients are determined; 5) the DCT filter coefficients are multiplied with the real number DFT coefficients of the input block; and 6) the inverse discrete cosine transform (IDCT) of the filtered DCT coefficients is performed by multiplying by IDCT coefficients to provide a block of lowpass-filtered pixels prepared for decimation. 
     The cutoff frequency of the lowpass filter is determined by the decimation ratio. For one exemplary embodiment, the cutoff frequency is π/3 for a 3:1 decimation and π/2 for a 2:1 decimation, where n corresponds to half of the sampling frequency. 
     A DCT domain filter in MPEG and JPEG decoders allows memory requirements to be reduced because the inverse quantizer and IDCT processing of blocks already exists in the decoder of the prior art, and only the additional scalar multiplication of DCT coefficients by the DCT domain filter coefficients is required. Therefore, a separate DCT domain filter block multiplication is not physically required in a particular implementation; another embodiment of the present invention simply combines the DCT domain filter coefficients with the IDCT processing coefficients. 
     For the exemplary down conversion system of the present invention, the horizontal filtering and decimations of the DCT coefficients were considered; and the following are two exemplary implementations for: 
     1. 1920H by 1080 V interlace to 640H by 1080 V interlace conversion (Horizontal 3:1 decimation). 
     2. 1280H by 720 V progressive to 640H by 720 V progressive conversion (Horizontal 2:1 Decimation) 
     Table 4 shows the DCT block mirror filter (weighting) coefficients; in Table 4 the numbers in the parenthesis are 10 bit  2 &#39;s complementary representations. The “*” of Table 4 implies an out of bound value for the 10 bit  2 &#39;s complement representation because the value is more than 1; however, as is known by one skilled in the art, the multiplication of the column coefficients of the block by the value indicated by the * can be easily implemented by adding the coefficient value to the coefficient multiplied by the fractional value (remainder) of the filter value. 
     
       
         
               
               
               
             
               
               
               
             
           
               
                   
                 TABLE 4 
               
               
                   
                   
               
               
                   
                 3:1 Decimation 
                 2:1 Decimation 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                 H[0] 
                  1.000000000000000 (511) 
                  1.0000000000000000 (511) 
               
               
                 H[1] 
                  0.986934590759779 (505) 
                  1.0169628157945179 (*) 
               
               
                 H[2] 
                  0.790833583171840 (405) 
                  1.0000000000000000 (511) 
               
               
                 H[3] 
                  0.334720213357461 (171) 
                  0.82247656390475166 (421) 
               
               
                 H[4] 
                 −0.0323463361027473 (−17) 
                  0.46728234862006007 (239) 
               
               
                 H[5] 
                 −0.0377450036954524 (−19) 
                  0.10634261847436199 (54) 
               
               
                 H[6] 
                 −0.0726889747390758 (37) 
                 −0.052131780559049545 (−27) 
               
               
                 H[7] 
                  0.00954287167337307 (5) 
                 −0.003489737967467715 (−2) 
               
               
                   
               
             
          
         
       
     
     These horizontal DCT filter coefficients weight each column in the block of 8×8 DCT coefficients of the encoded video image. For example, the DCT coefficients of column zero are weighted by H[0], and the DCT coefficients of first column is weighted by H[1] and so on. 
     The above discussion illustrates a horizontal filter implementation using a one-dimensional DCT. As is known in the digital signal processing art, such processing can be extended to two-dimensional systems. For a two-dimensional system, the input sequence is now represented as a matrix of values, showing the sequence to be periodic in the column sequence with period M, and periodic in the row sequence with period N, N and M being integers. A two-dimensional DCT can be implemented as a one dimensional DCT performed on the columns of the input sequence, and then a second one dimensional DCT performed on the rows of the DCT processed input sequence. Also, as is known in the art, a two-dimensional IDCT can be implemented as a single process. 
     G. Down Sampling 
     Down sampling is accomplished by the down fling processor  232  to reduce the number of pixels in the downconverted image. FIG. 5A shows the input and decimated output pixels for 4:2:0 chrominance type for 3:1 decimation. FIG. 5B shows the input and decimated output pixels for 4:2:0 chrominance type 2:1 decimation. Table 5 gives the legend identification for the Luminance an Chrominance pixels of FIG.  5 A and FIG.  5 B. The pixel positions before and after the down conversion of FIGS. 5A and 5B are the interlaced (3:1 decimation) and progressive (2:1 decimation) cases respectively 
     
       
         
               
               
             
           
               
                 TABLE 5 
               
               
                   
               
               
                 Symbol 
                 Pixel 
               
               
                   
               
             
             
               
                 + 
                 Luminance Before Decimation 
               
               
                 x 
                 Chrominance Before Decimation 
               
               
                 • 
                 Luminance After decimation 
               
               
                 Δ 
                 Chrominance After Decimation 
               
               
                   
               
             
          
         
       
     
     For down sampling of the interlaced image, which may be the conversion from a 1920 by 1080 pixel size to a 640 by 1080 pixel size, every third pixel is decimated on the horizontal axis. For the exemplary 3:1 decimation, there are three different macroblock types after the down conversion process. In FIG. 5A, original macroblocks (MBs) were denoted by MB 0 , MB 1 , MB 2 . The down sampled luminance pixels in MB 0  start at the first pixel in the original macroblock, but in MB 1  and MB 2  the down-sampled pixels start at the third and the second pixels. Also the number of down-sampled pixels in each macroblock are not the same. In MB 0 , there are 6 down-sampled pixels horizontally, but 5 pixels in MB 1  and MB 2 . These three MB types are repeating, therefore Modulo 3 arithmetic is to be applied. Table 6 summarizes the number of downsampling pixels and offsets for each input macroblock MB 0 , MB 1 , MB 2 . 
     
       
         
               
               
               
               
             
               
               
               
               
               
             
           
               
                   
                 TABLE 6 
               
               
                   
                   
               
               
                   
                 MB0 
                 MB1 
                 MB2 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 No. of Down Sampled 
                 6 
                 5 
                 5 
               
               
                   
                 Luminance Pixels 
               
               
                   
                 No. of Down Sampled 
                 3 
                 3 
                 2 
               
               
                   
                 Chrominance Pixels 
               
               
                   
                 Offset of 1st Down 
                 0 
                 2 
                 1 
               
               
                   
                 Sampled Luminance Pixel 
               
               
                   
                 Offset of 1st Down 
                 0 
                 1 
                 2 
               
               
                   
                 Sampled Chrominance Pixel 
               
               
                   
                   
               
             
          
         
       
     
     For downsampling of the progressive format image the signal is subsampled for every second sample horizontally. 
     While exemplary embodiments of the invention have been shown and described herein, it will be understood that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will occur to those is skilled in the art without departing from the spirit of the invention. Accordingly, it is intended that the appended claims cover all such variations as fall within the scope of the invention.

Technology Category: h