Abstract:
The invention relates to a method for detecting video frame types with median filtering, which proceeds a denoising step after caculating the comb factor of each pixel, to avoid incorrect judgment of the frame type resulting from excessive field difference and improve detection accuracy.

Description:
BACKGROUND OF THE INVENTION  
         [0001]    1. Field of the Invention  
           [0002]    The method for detecting video frame types with Median Filtering denoising step to distinguish comb factor from impure spots, then to determine frame types and improve detection accuracy.  
           [0003]    2. Description of the Prior Art  
           [0004]    The video picture that is commonly adopted at present is transmitted at 30 frames per second to produce continuous and dynamic images. Each frame consists of a plurality of scan lines (for instance, National Television System Committee—NTSC, standard is 525 scan lines). That is, 525 scan lines are transmitted in {fraction (1/30)} second for one frame.  
           [0005]    Said video frame is classified into two categories: interlaced frame and progressive frame. Scanning of the interlaced frame divides each frame into a top field and a bottom-field. The top field has an odd number of scan lines while the bottom-field has an odd number of scan lines. They are separately scanned at two times. For instance, the top-field is scanned first, then the-bottom field is scanned to generate a complete frame. For the progressive frames, all of the scanning lines are transmitted at the same time, so they are scanned consquentially individually one after one.  
           [0006]    Referring to FIG. 1( a ) and  1 ( b ) for an interlaced frame  10  and a progressive frame  11 . As the interlaced frame  10  is scanned at different times and is transmitted respectively for the top field (even number of scan lines) and the bottom-field (odd number of scan lines), a comb-shaped pattern is generated on the peripheral edges of the square picture  100  and the triangle picture  101  (generally called comb factor). The resolution is less desirable and video quality is poorer. While the whole progressive frame  11  is transmitted at the same time, therefore the comb factor as shown in FIG. 1( a ) does not occur.  
           [0007]    Based on previous discussion, it is obvious that the comb factor has great impact on resolution. Hence prior to video output, a detection process is performed to determine whether the input frame is an interlaced frame or a progressive frame. If the interlaced frame is detected, then a deinterlacing process is conducted to remove the comb factor to obtain a higher quality video. If the progressive frame is detected, the video may be directly output without deinterlacing.  
           [0008]    Referring to FIG. 2 for a traditional detection process. First, in step  201 , set the comb factor counter to be zero and input a frame F(n) for calculating the comb factor of pixels; then, in step  202 , apply all of the pixels to the frame function F(n); in step  203 , calculate the comb factor of the pixels (the equation for calculating the comb factor will be discussed later); in step  204 , determine whether the comb factor is above the threshold value; if “yes”, come to step  205  and increase the counter value by one; if “no”, come to step  206  to determine if it is the last comb factor; if it is, come to step  207 ; if “no”, repeat step  203  to step  206 ; in step  207 , determine whether the value in the counter is less than the threshold value; if yes, the frame is determined as a progressive frame at step  208 ; if no (i.e. the counter value is more than the threshold value), come to step  209  and determine the frame as an interlaced frame; finally end the detection process.  
           [0009]    [0009]FIG. 3 illustrates the calculation of a pixel comb factor in step  203  shown in FIG. 2. The pixel  30  to be calculated is located on the coordinate X in the picture. O-31 indicates a first adjacent pixel (b) and O-32 indicates a second adjacent pixel (e), then the equation for calculating the comb factor of the pixel  30  is as follows:  
           Comb Factor ( x, y )=( b−x )×( e−x )−( b−e ) 2    (Eq. 1)  
           [0010]    Of which, x is the pixel value of pixel  30  on the coordinate (x, y); b is the pixel value of the first adjacent pixel  31  on coordinate (x, y−1); e is the pixel value of the second adjacent pixel  32  on coordinate (x, y+1).  
           [0011]    Though a pixel could be determined whether it is a comb factor by comparing the value of each comb factor figured out with the formula with a fixed threshold value, then the type of the frame could be determined by the number of the comb factors (the number of the counters), this method sometimes still leads to wrong judgments. The reason is that when a pixel is greatly different from surrounding pixels in brightness, the comb factor value calculated with above formula shall be very big, so if there are some impure spots on videos, they may be wrongly determined to be comb factors due to the difference in brightness. For instance, if there are more impure spots on progressive frame videos, they may be wrongly determine to be interlaced frames.  
           [0012]    To solve the above mentioned problems, a method for detecting frame types with Median Filtering is offered in this invention, thus a more precise way of judging interlaced frames and progressive frames is available.  
         SUMMARY OF THE INVENTION  
         [0013]    The primary object of the invention is to provide a method for detecting video frame types with a denoising step to distinguish comb factor from impure spots, then to determine frame types. Thus the number of comb factors is accurately calculated and the possibility of wrong judgment is reduced to enhance the precision of frame type judgment.  
           [0014]    In order to achieve the foregoing object, invention for detecting frame types with Median Filtering is as follows: first, input a frame function F(n) and set the counter to zero; then apply all pixels to the function to determine whether the pixel is a comb factor; next, determine whether the comb factor is an impure spot by denoising; if it is, increasing the counter by  1 ; finally determine whether the frame is an interlaced frame or a progressive frames based on the number of the counter. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0015]    [0015]FIG. 1( a ) is a schematic picture of the video output of an interlaced frame;  
         [0016]    [0016]FIG. 1( b ) is a schematic picture of the video output of a progressive frame;  
         [0017]    [0017]FIG. 2 is a process flow for detecting frame types adopting a traditional detection technique;  
         [0018]    [0018]FIG. 3 is a schematic picture for calculating the comb factor value of a pixel of a frame;  
         [0019]    [0019]FIG. 4 is a process flow of a embodiment of the invention for detecting frame types with Median Filtering; and  
         [0020]    [0020]FIG. 5 is a process flow of another embodiment of the invention for detecting frames type with Median Filtering. 
     
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0021]    [0021]FIG. 4 is a process flow of a embodiment of the invention for detecting frame types with Median Filtering, comprising following steps:  
         [0022]    First, come to step  401  to set the counter to be zero, and input a frame function F(n) in a processor, these processes are substantially same as the ones of the conventional method set forth above, thus details are omitted.  
         [0023]    Then in step  402 , appling all pixels to function F(n), and get the comb factor value.  
         [0024]    proceeding step  403 , determining whether the comb factor value is more than the threshold value.  
         [0025]    Proceeding step  404  if the comb factor value is more than the threshold value,then set the value of Combmap 1  (x,y) to be 1.  
         [0026]    Proceeding step  405  if the comb factor value is not more than the threshold value, and set the value of Combmap 1  (x,y) to be zero.  
         [0027]    Proceeding step  406  to determine whether it is the comb map value of the last pixel.  
         [0028]    Coming to step  407 , if it is the comb map value of the last pixel.  
         [0029]    Repeating step  402  to  405  if it is not the comb map value of the last pixel, and until the comb map value of the last pixel is figured out.  
         [0030]    Then, come to step  407  for Median Filtering, that is, each pixel of combmap 1  is applied the following formula in step  408  to get the count. The formula is shown as follows:  
             Counts   =       ∑     i   =     -   1       1                       ∑     j   =     -   1       1                       M        (     i   ,   j     )       ·     combmap        (       x   +   i     ,     y   +   j       )                     (     Eq   .              2     )                               
 
         [0031]    The expantion of Eq. 2 becomes  
             counts   =       [         1       1       1           1       1       1           1       1       1         ]     ·     
                     [           CombMap        (       x   -   1     ,     y   +   1       )             CombMap        (     x   ,     y   +   1       )             CombMap        (       x   +   1     ,     y   +   1       )                 CombMap        (       x   -   1     ,   y     )             CombMap        (     x   ,   y     )             CombMap        (       x   +   1     ,   y     )                 CombMap        (       x   -   1     ,     y   -   1       )             CombMap        (     x   ,     y   -   1       )             CombMap        (       x   +   1     ,     y   -   1       )             ]               (     Eq   .              3     )                               
 
         [0032]    wherein, M and Combmap(x+i,y+j) are both 3×3 matrixes, and Combmap(x+i,y+j) is the comb map value of each pixel calculated before.  
         [0033]    After the counts is figured out, it is compared with Majority-th in step  409 . If it is more than the Majority-th, come to step  410  to add 1 to the counter; otherwise, come to step  411  to determine whether it is the counts of the last pixel, if it is, come to step  412 ; if not, repeat step  408  to  409 .  
         [0034]    In step  412 , determine whether the counter value is less than the counter threshold value. The counter value represents the number of comb factors. If it is less than the counter threshold value, it means the number of comb factors does not meet the standard of an interlaced frame, and it shall be determined as a progressive frame in step  412 ; if it is more than the counter threshold value, it means the number of comb factors has exceeded the standard value of an progressive frame, and it shall be determined as an interlaced frame in step  413 . Finally the detection flow ends.  
         [0035]    [0035]FIG. 5 is a process flow of another embodiment of this invention for detecting frame types with Median Filtering. It is different from the above case, i.e. it compares the counters with the Majority-th, and then inputs the result into the Compmap 2 . The case contains following steps:First,proceeding step  501  to set the counter to be zero and input a frame function F(n) into a processor, these processes are substantially same as the ones of the conventional method set forth above, thus details are omitted.  
         [0036]    Then come step  502  to apply all pixels to the function F(n) and get the comb factor value.  
         [0037]    proceeding step  503 , determining whether the comb factor value of pixel f(x,y) is more than the threshold value.  
         [0038]    Proceeding step  504  if the comb factor value is more than the threshold value,and set the value of Combmap 1 (x,y) to be 1.  
         [0039]    Proceeding step  505  if the comb factor value is not more than the threshold value, and set the value of Compmap 1 (x,y) to be zero.  
         [0040]    Proceeding step  506  to determine whether it is the comb map value of the last pixel.  
         [0041]    Coming to step  507 , if it is the comb map value of the last pixel.  
         [0042]    Repeating step  502  to  505  if it is not the comb map value of the last pixel, and until the comb map of the last pixel is figured out.  
         [0043]    Then come to step  507  for Median Filtering. First, in step  408 , each pixel of Combmap 1  is applied the formulas shown in Eq. 2 to get the counts.  
         [0044]    After calculating the counts, compare the counts with Majority-th in step  509  and input the result into factor map  2  that is a bit. In this step, the counts figured out by the formulas in Eq 3 are used to determine whether the pixel is a comb factor or an impure spot. In this case, if the counts of the pixel is more than the Majority-th, come to step  510  to set the value of Combmap 2 (x,y) to be 1; whease if the counts is less than the Majority-th, come to step  511  to set the value of Combmap 2  to be zero.  
         [0045]    In step  512 , determine whether Combmap 2  is 1; if it is, add 1 to the counter; if not, come to step  514  to determine whether it is the last value of compmap 2 ; if it is, come to step  515 ; if not, return to step  512 . Step  515  is used to determine whether the counter value is less than the counter threshold value. The number of counters represents the number of comb factor. If the counter number is less than counter threshold value, it means that the number of comb factors does not meet the standard of an interlaced frame, and it is shall be determined as a progressive frame (step  516 ). If the counter value is more than the counter threshold value, it means the number of comb factors in this frame has exceeded the standard, and it shall be determined as an interlaced frame (step  517 ), finally the detection flow ends.  
         [0046]    The detailed explanation discussed above is the method for detecting video frame types with Median Filtering. After a comb factor is figured out, the correspondind pixel is determined whether being a comb factor or an impure spot, and then the frame type is determined. In this way, the number of comb factors in a frame is accurately calculate, therefore, the possibility of wrong detection is reduced and the precision of the detection is enhanced.  
         [0047]    All in all, this invention is advanced both in objective and in effect and is valuable in commercialization. It is unprecedented for the moment and perfectly agrees to patent requirements, thus we submit an application.  
         [0048]    While the preferred embodiment of the invention has been set forth for the purpose of disclosure, modifications of the disclosed embodiment of the invention as well as other embodiment thereof may occur to those skilled in the art. Accordingly, the appended claims are intended to cover all embodiments which do not depart from the spirit and scope of the invention.