Patent Publication Number: US-7218794-B2

Title: Method for detecting grid in block-based compressed video

Description:
FIELD OF THE INVENTION  
   The present invention relates generally to video signal processing, and more particularly to detecting block grid in block-based compressed video for post-processing. 
   BACKGROUND OF THE INVENTION  
   Due to simplicity and efficiency, Discrete Cosine Transform (DCT) based compression techniques are dominant in video compression. Many popular video compression standards, such as MPEG-2, MPEG-4 and H.261, employ DCT techniques. The basic approach of a DCT based compression technique is to subdivide the image into 8×8 blocks and then individually transform, quantize, and encode each block. However, this block-based encoding technique introduces blocking artifacts between block boundaries because the DCT does not take the correlation between block boundaries into account. The blocking artifacts are typically the most noticeable picture degradation in DCT based coding systems. 
   Many post-processing algorithms have been proposed to remove the blocking artifacts of DCT-based compressed videos. Typically, such de-blocking algorithms need the precise location of the 8×8 grid because the de-blocking processes are applied near the grid where the blocking artifacts appear. De-blocking algorithms are designed for a fixed grid, assuming the grid location is known. However, in practice, grid positions can shift due to signal handling procedures, such as digital-analogue conversions and video signal transmission. Thus, when de-blocking algorithms are applied in real-life applications, such as TV, not only the blocking artifacts cannot be properly removed, but also other artifacts can be introduced if the algorithms&#39; designated grid location does not match the input video&#39;s actual grid location. As such, without the precise grid location being provided, conventional post-processing algorithms are ineffective in practice. 
   There is, therefore, a need for a grid detection method and system to control the post-processing for de-blocking. There is also a need for such grid detecting method and apparatus to be capable of accurately detecting whether there is a grid in the input video and computing the precise location of the detected grid. 
   BRIEF SUMMARY OF THE INVENTION  
   The present invention addresses the above needs. An object of the present invention is to provide a reliable grid detection method that can accurately detect the existence and the location of the grid in DCT compressed videos. To achieve that goal, in one embodiment the present invention provides a grid detection method and system to control the post-processing. The grid detecting method accurately detects whether there is a grid in the input video and compute the precise location of the grid if it exists. When a grid is detected in the input video, a post-processor is turned on and the de-blocking processing is applied on the grid detected by the grid detector. When no grid is detected, indicating that the input video is either an uncompressed video or an already de-blocked video, post-processing turned off to avoid degrading the picture quality. 
   In an embodiment, the grid detection method includes the steps of: computing horizontal and vertical second derivatives for all pixels of the input image; generating a horizontal second derivative zero-crossing mask and a vertical second derivative zero-crossing mask, by marking those pixels whose second derivatives have opposite signs with respect to those of their horizontal or vertical neighboring pixels; applying horizontal and vertical integral projections to the horizontal and vertical zero-crossing masks to generate respective projected one dimensional (1D) signals, respectively; generating local maximum masks by locating the local maximum of the two projected 1D signals; and determining grid location by computing the positions of the local maximum masks. 
   Such a grid detection method accurately detects whether there is a grid in the input video and computes the precise location of the grid if it exists. The results of grid detection can be used to control post-processing for de-blocking. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS  
     These and other features, aspects and advantages of the present invention will become understood with reference to the following description, appended claims and accompanying figures where: 
       FIG. 1A  shows an example application of a grid detection method according to the present invention; 
       FIG. 1B  shows a flowchart of the steps of embodiment of a grid detection method according to the present invention; 
       FIG. 2  shows a block diagram of an embodiment of a grid detection system according to the present invention; 
       FIG. 3  shows a diagram illustrating an example zero-crossing point of a continuous function; 
       FIG. 4  shows a diagram illustrating an example zero-crossing at the block boundary in a DCT compressed image; and 
       FIG. 5  shows a block diagram of an example H/V zero-crossing mask generator of  FIG. 2 , according to the present invention. 
   

   DETAILED DESCRIPTION OF THE INVENTION  
   While this invention is susceptible of embodiments in many different forms, there are shown in the drawings and will herein be described in detail, preferred embodiments of the invention with the understanding that the present disclosure is to be considered as an exemplification of the principles of the invention and is not intended to limit the broad aspects of the invention to the embodiments illustrated. 
   As noted above, in one embodiment the present invention provides a grid detection method that can be used to control the post-processing for de-blocking. Referring to  FIG. 1A , an example video processor  10  according to the present invention includes a grid detector  12  and a post-processor  14 . The grid detector  12  detects if the input video includes a grid and computes the location of the grid if it exists. If a grid is detected, then the post-processor  14  is turned on and de-blocking is performed based on the grid location provided by the grid detector. If no grid is detected, indicating that the input video is either an uncompressed video or a de-blocked video, the post-processor  14  is turned off to avoid degrading the picture quality. 
     FIG. 1B  shows a flowchart of the steps of the embodiment of a grid detection method implemented in the grid detector  12 , according to the present invention. The grid detection method is for processing video signals representing video image frames comprising pixels, in order to detect the existence and the positions of a block grid in each frame resulting from block-based transform coding. The grid detection method comprises the steps of: computing horizontal and vertical second derivatives for all pixels of the input image (step  20 ); generating a horizontal second derivative zero-crossing mask and a vertical second derivative zero-crossing mask, by marking those pixels whose second derivatives have opposite signs with respect to those of their horizontal or vertical neighboring pixels (step  22 ); applying horizontal and vertical integral projections to the horizontal and vertical zero-crossing masks to generate respective projected one dimensional (1D) signals, respectively (step  24 ); generating local maximum masks by locating the local maximum of the two projected 1D signals (step  26 ); and determining grid location by computing the positions of the local maximum masks (step  28 ). Implementation details of the above steps are described by example further below. 
     FIG. 2  shows a block diagram of an example embodiment of the grid detector  12  according to the present invention. The grid detector  12  includes a horizontal processing section and a vertical processing section. The horizontal processing section generates the horizontal position of a detected grid, and the vertical processing section generates the vertical position of a detected grid. Horizontal processing and vertical processing are independent of each other, and as such, they can be performed in any order, or in parallel. In the following description, a detailed explanation of the horizontal processing section is provided. The vertical processing section is similar to the horizontal processing section. 
   To help understanding, the following notations are used through the description, wherein: M denotes the image height, N denotes the image width, f(m,n) denotes the gray value of pixel (m,n) in an image, where m and n are the row and column indices, respectively, with 0≦m&lt;M and 0≦n&lt;N. Note that n represents the horizontal dimension of the image, and m represents the vertical dimension of the image frame. Further, for explanation purposes, and not limitation, a square grid block of dimensions (size) 8×8 pixels is used in the description herein. However, as those skilled in the art recognize, the present invention is useful with other grid block shapes and dimensions. 
   The horizontal processing section of the grid detector  12  includes a Horizontal Zero-Crossing Mask Generator  30 , a Horizontal Integral Projector  32 , a Local Maximum Mask generator  34 , and a Horizontal Shift Determination block  36 . The input video frame is first provided to a Horizontal (H) Zero-Crossing Mask generator  30  in the horizontal processing section. The H Zero-Crossing Mask generator  30  computes horizontal second derivatives for all pixels and marks the pixels that are the zero-crossing points of the horizontal second derivatives. 
   A zero-crossing point of a second derivative function can be explained by example as follows. For a continuous function F(x), a point x 0  is called a zero-crossing point of the second derivative F″ if F″(x 0 )=0 and F″(x) changes sign when x passes through the point x 0 .  FIG. 3  shows an example zero-crossing point x 0  of the continuous 1D function F(x) where F″(x 0 )=0 and F″(x) changes sign when x passes through the point x 0 . 
   Due to the discrete nature of image representations as pixels, the definition of zero-crossing for a continuous function cannot be directly used for images. However, the definition of zero-crossing can be modified for digital images as follows. Referring to  FIG. 4 , an image pixel (m 0 ,n 0 ) is a horizontal zero-crossing of the image f(m,n) if f h ″(m 0 ,n 0 ) and f h ″(m 0 ,n 0 −1) have opposite signs, where f h ″ denotes the horizontal second derivative of f. According to the above definition of zero-crossing for an image, the block boundaries, or grid, of a DCT compressed image have higher chances of occurring at (or near) zero-crossing points. This is because for two adjacent blocks, pixel values within each block are close in value to each other, while there is a pixel value jump (i.e., change in relative pixel value) across the block boundary. As shown by example in  FIG. 4 , this situation usually causes zero-crossing of the second derivative (e.g., block boundary between horizontal pixel position n 0 −1 and horizontal pixel position n 0 , in the image frame). 
   The block diagram in  FIG. 5  shows an example implementation of an embodiment of the H Zero-Crossing Mask generator  30 . In the H Zero-Crossing Mask generator  30 , a second derivative calculation block  40  calculates the horizontal second derivative f h ″ for each pixel. The second derivative calculation block  40  can be implemented e.g. as a high-pass filter with coefficients (1, −2, 1). Then a compute block  42  computes the product f n ″(m,n)·f h ″(m,n−1). And, a marking block  44  determines if f h ″(m,n)·f h ″(m,n−1)&lt;0, and if so, the image pixel at position (m,n) is marked as a zero-crossing pixel. 
   The H Zero-Crossing Mask generator  30  outputs a horizontal zero-crossing mask, Z h (m,n), wherein Z h (m,n) takes on value 1&#39;s at the zero-crossing pixels and 0&#39;s at non-zero-crossing pixels, wherein Z h (m,n) can be represented as:
 
 Z   h ( m,n )=1, if  f   h ″( m,n ) ·f   h ″( m,n− 1)&lt;0; and
 
 Z   h ( m,n )=0, otherwise.
 
   Although the number 0 is used in the criteria for marking the zero-crossing pixels, negative numbers with small absolute values can also be used. 
   Referring back to  FIG. 2 , the horizontal zero-crossing mask Z h (m,n) is supplied to the H Integral Projector  32 . The H Integral Projector  32  projects each vertical line of the mask Z h (m,n) onto the horizontal axis to produce a 1D signal, P h (n), that is a horizontal integral projection expressed as: 
   
     
       
         
           
             
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   The horizontal projection signal P h (n) is supplied to the Local Max Mask generator  34 . If X h (n) denotes the horizontal local maximum mask, for each position n, the Local Max Mask generator  34  compares the value P h (n) with other values of P h  in the interval centered at n with radius r e.g. 7 (i.e., [n−7, n+7]) to determine if it is the maximum (r is based on grid block size, wherein for an b×b grid block size r=b−1). 
   If P h (n) is the maximum within the example interval [n−7, n+7], then the position n is marked as a local maximum position, and the local maximum mask X h (n) is set to 1. Otherwise, X h (n) is set to 0. As indicated above, because the block grid positions have higher chance to be zero-crossing points, if a grid is detected, the local maximum mask X h (n) provides the detected grid&#39;s horizontal positions. 
   The horizontal local maximum mask X h (n) is then supplied to the H Shift Determination block  36  to determine the horizontal shift τ h  of the detected grid&#39;s horizontal position X h (n) from the standard grid&#39;s horizontal position. If S(m,n) denotes the standard grid, then S(m,n)=1 if either m or n can be divided by 8, and S(m,n)=0 otherwise. Though an 8×8 block of pixels is used for explanation herein, other block sizes and shapes can also be used. 
   Further, if S h (n) denotes the standard grid&#39;s horizontal position, then S h (n)=0 if n can be divided by 8, and S h (n)=0 otherwise. The H Shift Determination block  36  first computes the distances d h (i) between the horizontal local maximum mask X h (n) and the 8 possible shifted versions of the horizontal position of the standard grid S h (n) according to the example relation: 
   
     
       
         
           
             
               
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   Then H Shift Determination block  36  finds the smallest value among the eight d h (i)&#39;s. If d h (i 0 ) denotes the smallest distance, such that d h (i 0 )&lt;p·N/8, then the horizontal shift τ h =i 0 , wherein p is a percentage threshold value used to determine if a grid exists. For example, p=20% can be used. 
   If d h (i 0 )≧p·N/8, then no grid is detected, and τ h =−1. The computed horizontal shift τ h , together with the vertical shift τ v , is provided the Grid Position Determination block  38 , described further below. 
   As mentioned above, the vertical processing section is similar in function to the horizontal processing section, and it can operate independently. The vertical processing section generates the vertical shift τ v  of the detected grid position from the standard grid position. 
   Referring to the vertical processing section in  FIG. 2 , the input video frame is also supplied to a V Zero-Crossing Mask generator  46 . Similar to the H Zero-Crossing Mask generator  30 , the V Zero-Crossing Mask generator  46  generates the vertical zero-crossing mask Z v (m,n), which can be represented by relations:
 
 Z   v ( m,n )=1 if  f   v ″( m,n ) ·f   v ″( m− 1 , n )&lt;0;
 
 Z   v ( m,n )=0 otherwise;
 
   wherein f v ″ denotes the vertical second derivative, which can be calculated by using e.g. the high-pass filter (1, −2, 1), filtering along vertical direction. Once the vertical zero-crossing mask Z v (m,n) is generated, it is projected onto the vertical axis by a V Integral Projector  48 , to produce a 1D signal P v (m) represented as: 
   
     
       
         
           
             
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   The vertical projection signal P v (m) is supplied to a Local Max Mask generator  50  to generate the vertical local maximum mask X v (m). If P v (m) is the maximum within the e.g. interval [m−7, m+7], then the position m is marked as a local maximum position, and the local maximum mask X v (m) is set to 1. Otherwise, X v (m) is set to 0. The local maximum mask X v (m) provides the detected grid&#39;s vertical positions if the grid exists. 
   The vertical local maximum mask X v (m) is then provided to a V Shift Determination block  52  to determine the vertical shift τ v  of the detected grid&#39;s vertical position X v (m) from the standard grid&#39;s vertical position. If S v (m) denotes the standard grid&#39;s vertical position, then S v (m)=1 if m can be divided by 8, and S v (m)=0 otherwise. Similar to its counterpart in the horizontal processing section, the V Shift Determination block  52  first computes the distances d v (i) between the vertical local maximum mask X v (m) and the 8 possible shifted versions of the vertical position of the standard grid S v (m) according to the example relation: 
   
     
       
         
           
             
               
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   Then V Shift Determination block  52  finds the smallest value among the eight d v (i)&#39;s. If d v (i 0 ) denotes the smallest distance, when d v (i 0 )&lt;p·M/8, then the vertical shift τ v =i 0 , wherein p is a percentage threshold value used to determine if a grid exists. For example, p=20% can be used. If d v (i 0 )≧p·M/8, then no grid is detected, and τ v =−1. 
   In the final step of the grid detection, the Grid Position Determination block  38  uses the computed horizontal shift τ h  and vertical shift τ v , and determines the detected grid&#39;s position G(m,n). If either τ h =−1 or τ v =−1, then G(m,n)=0 for all 0≦m&lt;M and 0≦n&lt;N, indicating that a grid is not detected. Otherwise, G(m,n)=S(m−τ v , n−τ h ), wherein 0≦m&lt;M and 0≦n&lt;N. The detected grid position G(m,n) is the final output of the grid detection system. 
   Such a grid detector  12  according to the present invention accurately detects whether there is a grid in the input video and compute the precise location of the grid if it exists. The output of the grid detector  12  can be used to control post-processing for de-blocking as shown by example in  FIG. 1A . The grid detector  12  detects grids in the input video and computes the location of detected grids, as described. If a grid is detected, then the post-processor  14  performs de-blocking based on the detected grid location provided by the grid detector  12 . If no grid is detected, indicating that the input video is either an uncompressed video or a de-blocked video, the post-processor  14  is turned off to avoid degrading the picture quality. 
   The aforementioned apparatus/systems in  FIGS. 1 ,  2  and  5 , according to the present invention, can be implemented as program instructions for execution by a processor, as logic circuits, as ASIC, as firmware, etc., as is known to those skilled in the art. Therefore, the present invention is not limited to the example embodiments described herein. 
   The present invention has been described in considerable detail with reference to certain preferred versions thereof; however, other versions are possible. Therefore, the spirit and scope of the appended claims should not be limited to the description of the preferred versions contained herein.