Abstract:
Correcting deinterlaced video by determining whether the deinterlaced video has comb artifact areas, and correcting the comb artifact areas. The detection of comb artifacts includes comparing the differences in pixel values between adjacent rows with the differences in pixel values of alternate rows. The detection includes calculating comb artifact factors based on the differences, and comparing the median value for a group of pixels with a threshold to determine if there is an comb artifact at the pixel.

Description:
BACKGROUND 
     The invention relates to correcting video artifacts caused by interlacing. 
     With interlaced video a field of pixels for the odd lines are alternately transmitted with a field of pixels for the even lines. This can result in interlaced comb artifacts for an object in the field of view that has moved several pixels between the time that the odd and even fields were recorded. When the fields are combined into a single progressive frame the moving edge of the object can appear comb-like. Even in full-speed progressive motion display this comb-like artifact is visible as a moving jagged edge where a smooth or motion blurred edge would be expected. 
     SUMMARY 
     In one aspect, the invention features, in general, a method of correcting deinterlaced video by determining whether the deinterlaced video has comb artifact areas, and correcting the comb artifact areas. 
     In another aspect, the invention features, in general, a method of correcting deinterlaced video by determining whether the deinterlaced video has comb artifact areas by calculating a group value based on differences in pixel values between adjacent rows and the differences in pixel values of alternate rows for pixels in a group of pixels and comparing the group value (which could be a median value of factors determined for each pixel) with a threshold, and correcting the comb artifact areas. 
     Preferred embodiments of the invention may include one or more of the following features. In preferred embodiments the detection of comb artifacts includes comparing the differences in pixel values between adjacent rows with the differences in pixel values of alternate rows. Comb artifact detection also includes calculating the sum of squared differences between a subject pixel and pixels immediately above and below it, and also includes determining the sum of squared differences between the subject pixel and the pixel two rows above and the pixel two rows below it. The comparison can include determining the ratio of the sum of squared differences between a subject pixel and pixels immediately above and below it, and the sum of squared differences between the subject pixel and the pixel two rows above and the pixel two rows below it. Alternatively the comparison can include determining the difference of the sum of squared differences between a subject pixel and pixels immediately above and below it, and the sum of squared differences between the subject pixel and the pixel two rows above and the pixel two rows below it. The ratio or the difference thus determined can be compared with a predetermined (e.g., threshold) value. The ratios or the differences can also be determined for pixels in a group of pixels surrounding the subject pixel, and the ratios or differences (or a median for the ratios or differences) for the group can be compared with a predetermined (e.g., threshold) value. Alternatively, a pixel increment value can be assigned to each pixel of a group of pixels that has a ratio or difference that exceeds a predetermined value, and the sum of the pixel increment values for the group can then be compared with a predetermined value. The pixel increment values for pixels in the group can first be summed for pixels in the same column, and then the sums for each column can be summed for the group. In this way the group of pixels can be moved one column at a time to carry out a group comparison for all pixels in a row. After detecting the existence of comb artifacts, they can be corrected by computing a function based on the values of pixels above and below the subject pixel. The correction can include blending the odd and even fields in a comb artifact area, e.g., giving one-quarter weight to the pixels above and below a subject pixel and ½ to the subject pixel. Alternatively, the correction can include removing one of the fields in the comb artifact and replacing the missing pixel by averaging the pixels immediately above and below it. 
     In another aspect, the invention features, in general, a system for correcting deinterlaced video that includes a comb artifact detector that receives deinterlaced video and determines whether the deinterlaced video has comb artifact areas, and an artifact corrector responsive to the detector to correct the comb artifact areas and produce corrected video. 
     In another aspect, the invention features, in general, a program storage media storing computer executable instructions that cause a computer to determine whether deinterlaced video has comb artifact areas, and correct the comb artifact areas. 
     Embodiments of the invention may include one or more of the following advantages. Comb artifacts are automatically and quickly detected and corrected in deinterlaced video. 
     Other advantages and features of the invention will be apparent from the following description of an embodiment thereof. 
    
    
     DESCRIPTION OF DRAWINGS 
     FIG. 1 is the block diagram of a filter for correcting deinterlaced video. 
     FIG. 2 is the block diagram showing the components of the FIG. 1 filter. 
     FIG. 3 is a diagram of a deinterlaced field of pixels. 
     FIG. 4 is a diagram showing a subject pixel and pixels immediately above and below it and pixels two rows above and two rows below it. 
     FIG. 5 is a diagram showing a 5×5 neighborhood of pixels that is advanced along a row of pixels. 
    
    
     DETAILED DESCRIPTION 
     Referring to FIG. 1, there is shown filter  10  for receiving deinterlaced video  14  and providing corrected video  16 . 
     Referring to FIG. 2, it is seen that filter  10  includes comb artifact detector  18  and artifact corrector  20 . Filter  10 , comb artifact detector  18  and artifact corrector  20  can be implemented by a computer executing instructions on a storage medium. 
     Referring to FIG. 3, a portion  22  of a deinterlaced frame is shown. It includes odd lines of pixels  24  and even lines of pixels  26 . In this portion of the frame, the moving edge of an object is shown, and it is seen that the even rows of pixels are displaced by two pixels with respect to the odd rows of pixels, resulting in a so-called comb artifact. The edge of an object moving quickly in a horizontal direction across the frame could cause this artifact. Artifacts can also be created by vertical movement, in which case the artifacts are slightly different, with the odd line having an entirely different content than the adjacent even line. 
     In order to detect the existence of comb artifacts, comb artifact detector  18  determines a comb artifact factor (CAF) for each pixel in a frame and then compares the CAFs. The CAF is computed from pixel values in one or more layers of the image. For example, in the case of RGB, all three layers are used; for YUV, typically only the Y layer will be used. First even and odd differences are computed within each layer; then the differences are summed and squared across several layers. The odd differences are given by: 
     
       
           P   i+l   −P   i  and  P   1   −P   i−1   
       
     
     Where: 
     P i =the value of the subject pixel. 
     P i+l =the value of the pixel immediately above the subject pixel. 
     P i−l =the value of the pixel immediately below the subject pixel. 
     The even differences are given by: 
     
       
           P   i+2   −P   i  and  P   i   −P   i−2   
       
     
     Where: 
     P i+2 =the value of the pixel two rows above the subject pixel. 
     P i−2 =the value of the pixel two rows below the subject pixel. 
     The sum of the squares of the odd differences, Σ odd , is given by: 
     
       
         Σ odd =Σ( P   i+1   −P   i ) 2 +( P   i   −P   i−1 ) 2  for all layers.  
       
     
     The sum of the squares of the even differences, Σ even , is given by: 
     
       
         Σ even =Σ( P   i+2   −P   i ) 2 +(P i   −P   i−2 ) 2  for all layers.  
       
     
     CAF can be computed either as the difference between the sum of the squares of odd and even differences, CAF diff , or as the proportion between them, CAF prop , as indicated by the formulas below: 
     CAF diff =Σ odd −Σ even   
     CAF prop =Σ odd /Σ even   
     The CAF determines the likelihood that the subject pixel is part of a comb-artifact. In a highly textured area, both odd and even differences will be high; in a uniform area, both will be low. In either case, the CAF is generally low. In the comb-artifact area, the odd differences are much higher than the even differences, and the CAF is high. The sensitivity of the detection is adjusted by setting a threshold CAF above which a comb-artifact is detected. Artifact correction then takes place for subject pixels with a CAF above that threshold. Typical threshold values for CAF diff  might fall between 500 and 1000. Reasonable thresholds for CAF prop  might be 1.5-4. 
     Because pixels in an image can potentially have high CAFs by random chance, a further refinement of the technique is employed to avoid false-positives. For each subject pixel, comb artifact detector  18  calculates the median of the subject pixel CAF and the CAFs of a small pixel neighborhood surrounding the subject pixel. The pixel neighborhood can include all adjacent pixels, or it can include all pixels spaced by two rows or columns. The median value is then compared to the threshold CAF. A 50 percent median value can be employed; alternatively a “median” different than 50 percent can be chosen to provide a further parameter for adjusting sensitivity. 
     To quickly determine whether the median of CAFs for a rectangular neighborhood of pixels falls above or below a threshold, each pixel is assigned a pixel increment value of 1 if its CAF is above the threshold, otherwise a value of 0. The increment values of all pixels in the rectangular neighborhood are then totaled to arrive at a neighborhood increment value (NIV). If the NIV is above 50% of the number of pixels in the neighborhood, then the median of the CAFs for that neighborhood is above the threshold. Once again, a value other than 50% can be used to adjust sensitivity. 
     Finding the NIV can be accelerated, and its speed made independent of the size of the neighborhood, by appropriate subtotaling of pixel increment values. FIG. 5 illustrates determining the NIV for 5×5 neighborhoods for row  30 . Column increment values (CIV) comprising the sum of the pixel increment values for columns of 5 pixels along the entire length of row  30  are calculated and maintained. Column  32  is an example. To determine the total of pixel increments in the 5×5 neighborhood of e.g. pixel  34 , the 5 CIVs for the columns surrounding pixel  34  are totaled, arriving at a NIV for pixel  34 . 
     From the NIV for pixel  34 , the NIV of pixel  36 , immediately to the right, is determined by subtracting the CIV for column  32 , and adding the CIV for column  36 . Assuming all CIVs for row  30  are already computed, the NIVs for all pixels in row  30  are computed by repeatedly subtracting the leftmost CIV and adding the next CIV to the right. 
     After computing NIVs for row  30 , detector  18  advances to the next row, labeled  38 . The CIVs for row  38  are incrementally computed from the CIVs for row  30  by subtracting the pixel increment value from the top of each CIV and adding a new pixel increment value at the bottom. Detector  18  then uses these adjusted CIVs to compute NIVs for row  38 . 
     By computing NIVs and CIVs in this incremental fashion, detector  18  reduces the computations necessary for all but the topmost and leftmost NIVs to a total of two additions and two subtractions, regardless of the neighborhood size for which it is computing NIV&#39;s. As noted above, a comb artifact is identified by a NIV greater than 50% (or other specified %). 
     After artifact detector  18  has detected artifacts, the artifacts are corrected at artifact corrector  20 . Artifact corrector  20  can correct for artifacts by blending the odd and even fields in comb artifact areas during deinterlacing. For example, the blending can include giving one-quarter weight to the pixels above and below a subject pixel and ½ weight to the subject pixel. Alternatively artifact corrector  20  can remove one of the fields in the comb artifact area and replace the missing pixel by averaging the pixels immediately above and below it. For example, if the even field is being eliminated from FIG. 3, and, assuming that white pixel  28  in the even field has a CAF above a threshold (as identified by a marker), pixel  28  could be replaced with e.g.: 
     a) an average of the odd-field pixels above and below, 
     b) 0.5 of the value of pixel  28 , plus 0.25 of the values of the pixels above and below  28 , 
     c) a so-called Lanczos interpolation (which is well known in the art) using several pixels from the odd frame above and below pixel  28 , or 
     d) an average of the Lanczos interpolation and the original value for pixel  28 . 
     Filter  10  thus automatically detects and removes comb artifacts from deinterlaced video. 
     Other embodiments of the invention are within the scope of the appended claims.