Abstract:
A method and apparatus for downscaling video images to a lower resolution (e.g. from HDTV to SDTV) is presented. The method comprising the steps of frequency domain anti-aliasing filtering and downscaling the first video signal in a first direction corresponding with a line direction in the first video signal to obtain a downscaled video signal, and spatial domain downscaling the downscaled video signal in a second direction perpendicular to the first direction to obtain the second video signal. The method and apparatus of the invention are suitable for efficient and high quality decoding both progressive and any-type encoded interlaced signals.

Description:
CLAIM FOR PRIORITY/CROSS REFERENCE TO RELATED APPLICATION 
     This application claims priority to U.S. Provisional Application Ser. No. 60/292,715 filed May 22, 2001. The content of the above-identified application is incorporated herein by reference. 
    
    
     FIELD OF THE INVENTION 
     This invention relates to downscaling spatial resolution in video signals such as high definition television (HDTV) signals. More specifically, this invention relates to downscaling the resolution of HDTV signals to be commensurate with the resolution of standard definition television (SDTV). 
     BACKGROUND OF THE INVENTION 
     Television, since its introduction into the commercial markets, has become a ubiquitous product that has reached into every comer of daily life. Television, whether broadcast television or cable television, provides viewers with more information about changes in the world than any other news form or media. As such the number of televisions sets that are in operation is in the hundreds of millions. 
     Current television technology, termed Standard Definition Television (SDTV), is based on an analog technology that was developed and standardized in the mid-portion of the 20th century. These long established television broadcast standards for frequency allocation, format, etc., impose limits upon the amount of information that can be transmitted and, consequently, viewed by a user. Newer digital television technology, termed High Definition Television (HDTV), designed to overcome the limitations of SDTV, is able to increase the amount of the data transmitted by digitizing and compressing the television signal before transmission. A significant advantage of HDTV over SDTV is that the increased data transmission improves the clarity of the viewed image. The clarity is improved by transmitting an image having greater resolution than SDTV transmission. 
     As the number of HDTV transmissions begin to increase in conjunction with the existing SDTV transmissions, hundreds of millions of SDTV television sets must be adapted to receive the new HDTV signals. Adapting SDTV television sets to HDTV formats may be easily accomplished by adding a converter box, e.g., a set-top box, to spatially downscale the received HDTV signal to a format acceptable for viewing on the SDTV television set. Techniques to spatially downscale from HDTV to SDTV are well known in the art. 
     WO97/14252-A1 discloses a method and apparatus using the discrete cosine transform (DCT) to resize the image. To reduce an image, the method and apparatus exploit the convolution-multiplication property of the DCT to implement the anti-aliasing filter in the DCT domain, then the filter coefficients are operated on to produce DCT coefficients of the reduced-size image. 
     EP 0 781 052-A2 discloses a decoder for decoding MPEG video bitstreams encoded in any color space encoding format and outputting the decoded video bitstream to different size windows. Both MPEG decompression and color space decoding and conversion are performed on the bitstreams within the same decoder. The disclosed decoder may be programmed to output the decoded video bitstream in any of three primary color space formats comprising YUV 4:2:0, YUV 4:2:2 and YUV 4:4:4. The decoder may also output the decoded bitstream to different sized windows using DCT based image resizing. 
     SUMMARY OF THE INVENTION 
     An object of the invention is to provide a more advantageous resolution downscaling, in particular for encoded video signals including both field-type encoded groups of pixels and frame-type encoded groups of pixels. To this end, the invention provides a method and an apparatus according to the independent claims. Advantageous embodiments are defined in the dependent claims. 
     According to a first aspect of the invention, frequency domain anti-aliasing filtering and downscaling is performed in a first direction (e.g. horizontal) corresponding with a line direction in the first video signal and spatial domain downscaling is performed in a second direction (e.g. vertical) perpendicular to the first direction. The downscaling in the first direction may be performed prior to or during an inverse frequency transform operation. The invention is based on the insight that a given type of frequency domain anti-aliasing filter which is applied in the second direction for both field-type encoded groups of pixels and frame-type encoded groups of pixels corresponds to different filter types in the spatial domain. This is a consequence of the fact that field-type groups of pixels usually include two separate transform encoded fields (e.g. top field and bottom field) whereas frame-type groups of pixels usually include information corresponding to two fields mixed in one frame which is transform encoded as a whole. Filtering field-type and frame type encoded groups of pixels differently in the spatial domain may lead to significant errors arising during inverse motion compensation in the case that both field-type and frame-type encoded groups of pixels are present in the video signal. By frequency domain anti-aliasing filtering and downscaling in the line direction and spatial domain downscaling in the perpendicular direction, these errors are reduced. The method and apparatus of the invention are therefore suitable for handling interlaced video signals comprising mixed frame/field type groups of pixels, interlaced signals without mixed frame/field type encoded groups of pixels (e.g. only field type encoded groups of pixels) as well as progressive video signals with frame-type encoded groups of pixels without major modifications to the method or apparatus. 
     In a practical embodiment, spatial domain anti-aliasing filtering in the second direction is performed prior to the spatial domain downscaling in the second direction. 
     In an embodiment, the first video signal is downscaled prior to or during an inverse transform operation such as an inverse DCT (IDCT) which transform operation is followed by an inverse motion compensation prior to the spatial domain downscaling in the second direction. This has the advantage that errors which may be introduced by the motion vector downscaling have no effect on the inverse motion compensation in the second direction. The spatial domain downscaling in the second direction is preferably preceded by anti-aliasing filtering in the same direction. The spatial domain downscaling is preferably applied at frame level. This makes it possible to use a filter with long impulse response in the second direction to obtain a sharper frequency cutoff. Advantage of this embodiment is that distortions occurring at block edges due to block-based filtering are present only in the first direction. As inverse motion compensation is performed on one-directional downscaled pictures the memory size required for reference field/frame storing is reduced compared with traditional full spatial domain scheme. The memory reduction depends on horizontal scaling factor. 
     Preferably, the spatial domain downscaling is performed prior to the inverse motion compensation. Due to the vertical spatial domain downscaling prior to inverse motion compensation, the memory size needed for storing a reference field/frame for the inverse motion compensation is reduced to e.g. half the size in the case the downscaling reduces the size of the field/frame with 50%. This memory size corresponds to the memory size which is needed for a comparable bi-directional frequency domain downscaling. 
     In an alternative embodiment, field-type encoded groups of pixels are anti-aliasing filtered in both directions in the frequency domain rather than one direction in the frequency domain and the other in spatial domain. For each frame-type encoded group of pixels horizontal frequency domain anti-aliasing filtering and vertical spatial domain anti-aliasing filtering is performed. In this embodiment, the same frequency domain filter can be applied in horizontal direction for field-type encoded groups of pixels and frame-type encoded groups of pixels. The spatial domain filter which is used in vertical direction for frame-type encoded groups of pixels has to correspond to the frequency domain filter which is used in vertical direction for field-type encoded macroblocks. Due to the vertical downscaling in spatial domain prior to inverse motion compensation, the memory size needed for storing a reference field/frame for the inverse motion compensation corresponds to the memory size which is needed for a comparable bi-directional frequency domain downscaling. The performance of this embodiment is higher because vertical spatial domain filtering, which is usually a slow procedure, is only performed on frame-type groups of pixels and not on field-type groups of pixels. Each frame-type group of pixels is filtered in frequency domain only in the first direction and then downscaled in the first direction during scalable IDCT. After all groups of pixels are decoded in this way, the mixed field information can be separated and each group of pixels is filtered and downscaled in spatial domain in the second direction prior to motion compensation. The field-type group of pixels is frequency domain filtered in both directions but downscaled in one direction in the frequency domain and in the other direction in the spatial domain prior to the inverse motion compensation. 
     The groups of pixels may be blocks of pixels or macroblocks. In the case of MPEG-2 each 16×16 macroblock consists of four 8×8 blocks of pixels. The interlaced signals can be encoded by the two different modes in e.g MPEG-2: the first is with field type of picture and the second one is with frame type of picture. In the first case each field of picture is coded separately and mixed field/frame macroblock mode is not used. In the second case (the most commonly used) each picture is coded at progressive manner, i.e. two fields are mixed and coded together. For this case the mixed macroblock mode is used. So if one uses the straightforward bi-directional frequency domain down conversion scheme for second way encoded interlaced signals, it leads to error propagation during motion compensation and significant visual quality losses. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the drawings: 
         FIG. 1  illustrates an exemplary HDTV transmitting and receiving system. 
         FIG. 2  illustrates exemplary HDTV and SDTV display formats; 
         FIG. 3  illustrates an exemplary HDTV receiving system and SDTV display system; 
         FIG. 4   a  illustrates a functional block diagram of an exemplary MPEG decoding system; 
         FIG. 4   b  depicts an illustrative block diagram of an exemplary MPEG decoding system; 
         FIG. 5  illustrates an exemplary embodiment of a decoding system in accordance with principles of the invention; 
         FIG. 6   a  illustrates an exemplary block diagram of a decoding system in accordance with principles of the invention; 
         FIG. 6   b  depicts a functional block diagram of part of the exemplary decoding system as shown in  FIG. 6   a , and 
         FIG. 6   c  depicts a functional block diagram of an exemplary motion vector downscaling for use in the exemplary decoding system as shown in  FIG. 6   a.    
     
    
    
     It is to be understood that these drawings are solely for purposes of illustrating the concepts of the invention and are not intended as a definition of the limits of the invention. It will be appreciated that the same reference numerals, possibly supplemented with reference characters where appropriate, have been used throughout to identify corresponding parts. 
     DETAILED DESCRIPTION OF THE INVENTION 
     To understand and appreciate the novel features of the present embodiment, which involve scaling HDTV decoded signals for display on Standard Television screens, it is first necessary to discuss conventional HDTV processes and the problems associated therewith.  FIG. 1  illustrates a typical HDTV system. As illustrated, a digital television signal produced by signal generator  101  composed typically of an 8×8 matrix of 64 pixel elements, is compressed by MPEG encoder  103 . MPEG encoding is based on the Discrete Cosine Transformation (DCT), a mathematical operation similar to Fourier transformation and well known in the art. MPEG encoder  103  performs, among other operations, a conversion of an exemplary 8×8 matrix of pixels, represented by signal  102 , into an 8×8 matrix of coefficients, represented by signal  104 . As is known, the resultant DCT transformed matrix stores high-frequency information in the top-left comer of the matrix and the low-frequency information in the bottom-right corner of the matrix. The DCT transformed matrix is then quantized so that 8 bits i.e., one byte, are used to describe the values in each matrix element. The quantized matrix is transmitted, in this illustrative example, by TV transmitter  105  through transmitting antenna  106 . Digital video compression techniques, such as MPEG -2, MPEG-4, MPEG-7, which are standards specified by the Moving Pictures Experts Group (MPEG), are well known in the art and need not be discussed in detail herein. 
     Returning to  FIG. 1 , the transmitted digital signal  108  is received by receiving antenna  110  and processed by TV receiver  120 , which includes tuner  125 . Tuner  125  is used to isolate a specific HDTV signal from the plurality of HDTV and SDTV signals received. The isolated signal is then processed by decoder  140 , e.g., an MPEG decoder, which decodes the digitally transmitted signal  130  into displayable signal  145 . Using, for example MPEG decoding, decoder  140  decodes the received signal and returns the transmitted coefficients to a stream of pixel data ordered by lines and rows. Display driver  150  generates appropriate Red (R), Green (G) and Blue (B) colors signal for display on high-resolution screen  160  based on the received data. 
     To achieve higher resolution, HDTV images are created with a high resolution. In one case, an image is transmitted with 1920 pixels in each horizontal line and there are 1080 lines, i.e., a resolution of 1920×1080. In a second case, an image is transmitted with 1280 pixels per line and 720 lines, i.e., 1280×720. SDTV television, on the other hand, has a resolution significantly less than that of HDTV. For example, the television transmission system in the United States and Japan, the SDTV system NTSC consists of a resolution of approximately 720×480, i.e., 720 pixels for each of 480 lines. Europe employs the PAL system which uses still a different resolution, i.e., 720×576. 
       FIG. 2  illustrates the image viewing area of a typical NTSC SDTV image superimposed on a HDTV image. In this illustrative example, the viewing area of a transmitted HDTV image is depicted as area  205  and the SDTV image is depicted as area  210 . As is illustrated, a significant portion of the HDTV image is lost as only that portion of the HDTV image overlapping the SDTV image is viewable on an SDTV screen. 
     To enable the display of HDTV signals on SDTV screen, the HDTV signal is “downscaled” to compress the HDTV signal.  FIG. 3  illustrates the introduction of scaler  170 , in the system of  FIG. 1  to scale digital signal  145  into scaled signal  155  for viewing on SDTV screen  190 . In this case, scaler  170  essentially performs a two-dimensional scaling of the signal  145  to reduce image  205  of  FIG. 2  to fit within the bounds of image  210 . That is, scaler  170  divides, in this illustrative example, image  205  horizontally by the ratio: 
               1920   720     =   2.66         
and vertically by the ratio:
 
     
       
         
           
             
               1080 
               486 
             
             = 
             2.22 
           
         
       
     
     Scaler  170  may further be programmable to appropriately downscale alternative HDTV resolutions. CPU  180  is used illustratively to program scaler  170  to the appropriate downscaling ratios. 
     However, decoding and downscaling HDTV signals in the manner disclosed requires a full decoding of the HDTV signal and significant resources.  FIG. 4   a  illustrates an exemplary decoder  140 , e.g., MPEG decoder, which is well known in the art and briefly described herein. As illustrated, digital signal  130  is processed by Huffman decoder  425 . The Huffman decoded signal is then processed by inverse quantizer  405 . Signal  407  is then processed by Inverse DCT (IDCT)  410  to convert the, typically transmitted 8×8 matrix of 64 coefficients into an 8×8 matrix of 64 pixels. The converted signal  408  is then combined with a signal to uncompress the transmitted image by restoring stationary image data and to inverse ( 436 ) the motion compensation that was originally applied. The resultant combined signal is now a digital image that is uncompressed and motion compensated. A link between the Huffman decoder  425  and the inverse motion compensation block  436  shows that the Huffman decoder  425  decodes motion vector data prior to their using for inverse motion compensation. The digital image is next applied to anti-aliasing filter  435  to filter the high-frequency components from the image. Anti-aliasing filtering as such is well-known in the art and may e.g. be implemented as a low-pass Finite Impulse Response filter. Anti-aliasing filter  435  softens the edges of the data items within the digital images. Output signal  145  includes pixel information that is representative of video lines used to display an image. 
       FIG. 4   b  illustrates the video memory  420  needed in decoder  140  to perform inverse motion compensation. In this illustrative example, each image is stored on a “page” of video memory. Memory page  420   a  thus includes pixel information associated with a first image, memory  420   b  includes pixel information associated with a second image and memory  420   n  includes the pixel information associated with an “n-th” image. As will be appreciated, storage of each video image requires significant video memory. For example, storing an image having resolution 1920×1080 requires over 2 Megabytes of memory storage. 
       FIG. 5  illustrates the replacement of decoder  140  by AFD (All Format Decoder)  505  in accordance with an embodiment of the invention. In this illustrative embodiment, AFD  505  receives the digital signal  130  and converts it into scaled signal  520 . In this case, AFD  505  horizontally scales digital signal  130  to achieve a resolution comparable to the standards of an SDTV image. For example, AFD  505  horizontally downscales digital signal  130  by a factor of two (e.g., resolution  1920  to  960 ). Horizontally scaled signal  520  is then vertically scaled by scaler  170  to achieve a resolution comparable to the standards of an SDTV image. For example, scaler  170  vertically downscales horizontally scaled signal  520  by a factor of two i.e., resolution 1080 to 540. Accordingly, the downscaled image has a resolution of 980×540. 
     The use of AFD  505  to downscale the digital signal  130  horizontally is advantageous, as less processing power is needed because digital signal  130  is not decoded at a full resolution and significantly less video memory is necessary to store uncompressed motion compensated video data. Processing power requirements of AFD  505  are significantly reduced, as a selectively chosen reduced data set, e.g., a 4×8 matrix of 32 elements is processed rather than a conventional 8×8 matrix of 64 elements. Further, significantly less video memory is necessary to store the scaled images, as the complete decoded image is not stored, but, rather, only the selectively chosen reduced data set. Reduced memory is illustrated as memory  510   a  through  510   n  in  FIG. 5 . In this case, the video memory requirements to store a horizontally scaled image for inverse motion compensation performing are approximately one Megabyte. In the case that the macroblocks are spatially downscaled prior to the inverse motion compensator, even further reduced data sets are processed, e.g. 4×4 matrix of 16 elements. The output of the AFD  505  is in that case a frame which has been downscaled in both directions thereby making the scaler  170  redundant. In this case, the video memory requirements to store a horizontally and vertically scaled image for inverse motion compensation performing are approximately one-half Megabyte. 
       FIG. 6   a  depicts an exemplary functional block diagram of AFD  505 . In this illustrative diagram, the digital signal  130  is first processed by the Huffman decoder  425 , and then processed by an inverse quantizer and frequency domain filter  610 . The output of quantizer/filter  610  is signal  612 . Signal  612 , as will be shown, has a filtered characteristic similar to the filtered characteristic achieved by anti-aliasing filter  435 . Signal  612  is next processed by scalable IDCT  615 , which converts the exemplary  64  filtered coefficient elements of the signal  612  to a horizontally scaled signal composed of selectively chosen, for example, 32 pixel elements. The output of the scalable IDCT  615  is then scaled in vertical direction in spatial domain vertical downscaler  511  and merged with a signal from scalable motion compensator  650  to restore the stationary information within an image and inverse the effect of motion compensation. Motion vectors for use in the motion compensator  650  are derived from the Huffman decoder  425  via a motion vector scaler  513 . Output signal  520  is a signal having resolution spatially downscaled to be substantially compatible with SDTV television sets. 
       FIG. 6   b  illustrates a functional block diagram of part of the exemplary decoder of  FIG. 6   a . In this functional embodiment of the decoder, the filtered signal  612  produced by the quantizer/filter  610 , is processed by the IDCT and Horizontal scaler  615 , which transforms the set of coefficients to a reduced set of pixels. In the case interlaced material includes mixed field/frame mode of macroblocks, the decoder can be programmed to spatial domain downscaling the image vertically on macroblock level or on frame level. If macroblock level is chosen, after IDCT  630  each filtered and horizontally downscaled macroblock is processed by spatial filter and scaler in vertical direction if it is frame-type coded. If macroblock is field-type coded it may be processed by scaler without filtering because it may already be filtered in both directions in the frequency domain. Note that vertical frequency domain filter used for field-type coded macroblocks must correspond to spatial domain filter used for frame-type encoded macroblock in order to reduce prediction distortions during inverse motion compensation. If frame level vertical spatial domain downscaling is chosen, any-type coded macroblocks are downscaled horizontally in the IDCT  630  and thereafter processed by motion compensator  650 . After performing motion compensation the spatial domain filter and scaler  170  are necessary to spatially downsize the image vertically. 
       FIG. 6   c  illustrates a functional block diagram of the motion vector downscaler  513 . The motion vector  122  is first processed by Huffman decoder  425 , then downscaled horizontally by horizontal motion vector scaler  514 , vertically downscaled by vertical motion vector scaler  515  and processed by motion compensator  650 . In the case of frame level vertical spatial downscaling, a motion vector has to be downscaled only in vertical direction by vertical motion vector scaler  515 . 
     The selection of frequency domain and corresponded spatial domain filters can now be shown to be related to the convolution—multiplication properties of Discrete Cosine Transform. As is known in the art, the DCT possesses convolution—multiplication properties similar to the Discrete Fourier Transform (DFT). Then for a one-dimensional real sequence a(n), n=0 . . . N−1, and for a one-dimensional real and even sequence h(n), n=−N . . . N−1, it is known that if
 
 F   c ( n )= A   c ( n ) H   f ( n ), for  n= 0  . . . N− 1  [1]
         where F c (n) is the N-point DCT of f(n);
           A c (n) is the N-point DCT of the real sequence of a(n);
 
and
   H f (n) is the 2N-point DFT of h(n);   
           then
 
 f ( k )= a ( k )* h ( k ), for  k= 0  . . . N− 1;  [2]
 
where * denotes symmetric convolution operator which can be consider as symmetrically folded result of 2N-length cyclic convolution of sequences h(k) which is odd symmetry sequence expanded to even length by zero and even symmetry sequence ā(k): can be described as next:
       

     
       
         
           
             
               
                 a 
                 _ 
               
               ⁡ 
               
                 ( 
                 k 
                 ) 
               
             
             = 
             
               { 
               
                 
                   
                     
                         
                       ⁢ 
                       
                         a 
                         ⁡ 
                         
                           ( 
                           k 
                           ) 
                         
                       
                     
                   
                   
                     
                         
                       ⁢ 
                       
                         
                           k 
                           = 
                           0 
                         
                         , 
                         1 
                         , 
                         … 
                         ⁢ 
                         
                             
                         
                         , 
                         
                           N 
                           - 
                           1 
                         
                       
                     
                   
                 
                 
                   
                     
                         
                       ⁢ 
                       
                         
                           a 
                           ⁡ 
                           
                             ( 
                             
                               
                                 - 
                                 1 
                               
                               - 
                               k 
                             
                             ) 
                           
                         
                         , 
                       
                     
                   
                   
                     
                         
                       ⁢ 
                       
                         
                           k 
                           = 
                           
                             - 
                             N 
                           
                         
                         , 
                         
                           
                             - 
                             N 
                           
                           + 
                           1 
                         
                         , 
                         … 
                         ⁢ 
                         
                             
                         
                         , 
                         
                           - 
                           1 
                         
                       
                     
                   
                 
               
             
           
         
       
     
     This relational property between multiplication in the frequency domain and convolution in the time domain can be extended to the two-dimension case as: if
 
 F   c ( n,m )= A   c ( n,m ) H   f ( n,m ); for  n,m= 0  . . . N− 1;  [3]
 
,then
 
 f ( k,l )= a ( k,l )* h ( k,l ); for  k,l= 0  . . . N− 1   [4]
 
where * denotes two-dimension symmetric convolution operator; F c (n,m) is the two-dimensional N×N DCT of f(n,m), n,m=0 . . . N−1; A c (n,m) is the two-dimensional N×N DCT of a(n,m), n,m=0,N−1; H f (n,m) is the two-dimension 2N×2N DFT of h(n,m), n,m=−N . . . N−1.
 
     As will be appreciated, the two-dimension DCT of the real sequence of a(k,l) creates a matrix wherein the lower frequency elements are contained in the upper left of the matrix and the higher frequency element are contained in the lower right of the matrix. Now, according to equations 3 and 4, filtering in the DCT domain in both directions can be realized by multiplying the received DCT coefficients by a special filter matrix. As an example, the filter matrix of a 3-tap low-pass filter, for example, for impulse response h(n)={0.25,0.5,0.25} in both directions can be obtained the next way. According to equation 1 the frequency response of indicated filter H N (n) can be obtained by computation of DFT of h 2N (n), odd symmetric sequence expanded to 2 N-length by zeros. Two-dimension frequency response can be consider as:
 
 HH   N   =H   N   {circle around (×)}H   N   T ,
 
where {circle around (×)} denotes kronecker multiplication operator. Therefore for filter h(n) the multiplication matrix will be:
 
     
       
         
           
             
               H 
               ⁢ 
               
                   
               
               ⁢ 
               
                 H 
                 N 
               
             
             = 
             
               [ 
               
                 
                   
                     1 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     0.962 
                   
                   
                     0.925 
                   
                   
                     0.821 
                   
                   
                     0.665 
                   
                   
                     0.481 
                   
                   
                     0.297 
                   
                   
                     0.141 
                   
                   
                     0.037 
                   
                 
                 
                   
                     0.854 
                   
                   
                     0.821 
                   
                   
                     0.729 
                   
                   
                     0.59 
                   
                   
                     0.427 
                   
                   
                     0.263 
                   
                   
                     0.125 
                   
                   
                     0.032 
                   
                 
                 
                   
                     0.691 
                   
                   
                     0.665 
                   
                   
                     0.59 
                   
                   
                     0.478 
                   
                   
                     0.346 
                   
                   
                     0.213 
                   
                   
                     0.101 
                   
                   
                     0.026 
                   
                 
                 
                   
                     0.5 
                   
                   
                     0.481 
                   
                   
                     0.427 
                   
                   
                     0.346 
                   
                   
                     0.25 
                   
                   
                     0.154 
                   
                   
                     0.073 
                   
                   
                     0.019 
                   
                 
                 
                   
                     0.309 
                   
                   
                     0.297 
                   
                   
                     0.263 
                   
                   
                     0.213 
                   
                   
                     0.154 
                   
                   
                     0.095 
                   
                   
                     0.045 
                   
                   
                     0.012 
                   
                 
                 
                   
                     0.146 
                   
                   
                     0.141 
                   
                   
                     0.125 
                   
                   
                     0.101 
                   
                   
                     0.073 
                   
                   
                     0.045 
                   
                   
                     0.021 
                   
                   
                     
                       5.574 
                       · 
                       
                         10 
                         
                           - 
                           3 
                         
                       
                     
                   
                 
                 
                   
                     0.038 
                   
                   
                     0.037 
                   
                   
                     0.032 
                   
                   
                     0.026 
                   
                   
                     0.019 
                   
                   
                     0.012 
                   
                   
                     
                       5.574 
                       · 
                       
                         10 
                         
                           - 
                           3 
                         
                       
                     
                   
                   
                     
                       1.449 
                       · 
                       
                         10 
                         
                           - 
                           3 
                         
                       
                     
                   
                 
               
               ] 
             
           
         
       
     
     Accordingly, the frequency domain quantizer/filter can be combined with the inverse quantization function by prior merging of the quantization matrix with the filter matrix H(n, m). More specifically, if the filter matrix is denoted as HH N  as:
 
 HH   N   └hh   n,m ┘; for  n,m= 0  . . . N− 1
 
     And the Quantization matrix can be described as:
 
 Q   N   =└q   k,l ┘; for  k,l= 0  . . . N− 1
 
     Then the combined Quantization-Filtering matrix can be described as:
 
 C   N   =└q   n,m   hh   n,m ┘; for  n,m= 0  . . . N− 1
 
     It was indicated above that for sequences with mixed field/frame-type encoded macroblocks the frame-type encoded macroblocks must be filtered in frequency domain only in horizontal direction and in spatial domain in vertical direction. Also for frame level spatial vertical downscaling all macroblocks must be filtered in frequency domain only in horizontal direction. In that cases the filter matrix of h(n)={0.25,0.5,0.25} is: 
     
       
         
           
             
               
                 H 
                 f 
               
               ⁡ 
               
                 ( 
                 
                   n 
                   , 
                   m 
                 
                 ) 
               
             
             = 
             
               [ 
               
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
                 
                   
                     1.0 
                   
                   
                     0.962 
                   
                   
                     0.854 
                   
                   
                     0.691 
                   
                   
                     0.5 
                   
                   
                     0.309 
                   
                   
                     0.146 
                   
                   
                     0.038 
                   
                 
               
               ] 
             
           
         
       
     
     While there have been shown and described and pointed out fundamental novel features of the present invention as applied to preferred embodiments thereof, it will be understood, that various omissions and substitutions and changes in the methods described may be made by those skilled in the art without departing from the scope of the present invention. Furthermore, although, MPEG decoding is discussed, herein, with regard to HDTV transmission, it will be appreciated by those skilled in the art, that the inventive concept disclosed herein is not limited solely to MPEG coding/decoding, but is applicable to other digital TV coding/decoding techniques. 
     It is expressly intended that all combinations of those elements and/or method steps which perform substantially the same function in substantially the same way to achieve the same results are within the scope of the invention. Substitutions of elements from one described embodiment to another are also fully intended and contemplated. 
     It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word ‘comprising’ does not exclude the presence of other elements or steps than those listed in a claim. The invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a device claim enumerating several means, several of these means can be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.