Motion-compensated temporal filtering based on variable filter parameters

Abstract

Systems and devices for, and methods of, motion-compensated temporal filtering based on variable filter parameters. A method embodiment includes (a) determining, by a processor having memory, a pixel-related residue image based on a set of differences between a current pixel intensity of a current frame and a corresponding pixel intensity of a previous frame, wherein the corresponding pixel intensity is augmented by a motion-compensated vector of the previous frame; (b) determining an intensity weight based on the determined pixel-related residue image and a temporal filtering parameter; and (c) filtering the pixel intensity of the current frame based on the determined intensity weight and the motion compensated vector of the previous frame.

What is claimed is: 
     
         1 . A method comprising:
 determining, by a processor having memory, a pixel-related residue image based on a set of differences between a current pixel intensity of a current frame and a corresponding pixel intensity of a previous frame;   determining an intensity weight based on the determined pixel-related residue image and a filtering parameter, wherein the filtering parameter provides, via minimizing a mean-square difference error, a de-noising effect based on noise level;   filtering the pixel intensity of the current frame based on the determined intensity weight, the pixel intensity of the previous frame, and a standard deviation parameter; and   determining a filtered pixel intensity vector based on the filtered pixel intensity of the current frame.   
     
     
         2 . The method of  claim 1  further comprising:
 generating a second filtering parameter by subsequently revising the filtering parameter based on a set of previously determined residue images via tracking a count of frames. 
 
     
     
         3 . The method of  claim 2  further comprising:
 apportioning according to a resulting square-root of each residue image of the set of previously determined residue images. 
 
     
     
         4 . The method of  claim 2  wherein determining a filtered pixel intensity vector based on the filtered pixel intensity of the current frame is further based on the generated second filtering parameter. 
     
     
         5 . The method of  claim 1  further comprising:
 determining optimal values of the filtering parameter based on whether increasing the filtering parameter provides a de-noising effect without over-smoothing. 
 
     
     
         6 . The method of  claim 1  further comprising:
 determining optimal values of the filtering parameter based on whether increasing the filtering parameter provides a de-noising effect without generating artifacts. 
 
     
     
         7 . The method of  claim 1  wherein the filtering parameter is a spatial statistical representation of pixel intensity. 
     
     
         8 . The method of  claim 7  wherein the filtering parameter is based on a variance of image intensity within a region associated with the current pixel. 
     
     
         9 . The method of  claim 1  wherein determining a filtered pixel intensity vector based on the filtered pixel intensity of the current frame is further based on a spatial weighting distribution. 
     
     
         10 . A method comprising:
 determining, by a processor having memory, a pixel-related residue image based on a set of differences between a current pixel intensity of a current frame and a corresponding pixel intensity of a previous frame;   determining a set of intensity weights based on the determined pixel-related residue image and a temporal filtering parameter, wherein the filtering parameter provides, via minimizing a mean-square difference error, a de-noising effect based on noise level;   determining a set of spatial weights based on a set of neighboring pixels;   filtering the pixel intensity of the current frame based on the set of determined intensity weight, the pixel intensity of the previous frame, a standard deviation parameter, and the determined set of spatial weight; and   determining a filtered pixel intensity vector based on the filtered pixel intensity of the current frame and a spatial weighting distribution.   
     
     
         11 . The method of  claim 10  wherein the set of spatial weights is based on a set of neighboring pixels wherein each pixel in the set of neighboring pixels has a different filtering parameter based on local features of the current frame. 
     
     
         12 . The method of  claim 10  wherein the set of spatial weights is based on a set of neighboring pixels wherein the weight is attenuated distal from the pixel around which the intensity vector is being determined. 
     
     
         13 . The method of  claim 10  further comprising:
 determining a second filtering parameter via attenuating the determined set of intensity weights based on the determined spatial weights and tracking a count of frames. 
 
     
     
         14 . The method of  claim 13  further comprising:
 apportioning according to a resulting square-root of each residue image of a set of previously determined residue images. 
 
     
     
         15 . The method of  claim 13  wherein determining a filtered pixel intensity vector based on the filtered pixel intensity of the current frame is further based on the determined second filtering parameter. 
     
     
         16 . A device comprising:
 a processor, configured to:
 determine a pixel-related residue image based on a set of differences between a current pixel intensity of a current frame and a corresponding pixel intensity of a previous frame; 
 determine an intensity weight based on the determined pixel-related residue image and a filtering parameter, wherein the filtering parameter provides, via minimizing a mean-square difference error, and a de-noising effect based on noise level; 
 filter the pixel intensity of the current frame based on the determined intensity weight, the pixel intensity of the previous frame, and a standard deviation parameter; and 
 determine a filtered pixel intensity vector based on the filtered pixel intensity of the current frame and a spatial weighting distribution. 
   
     
     
         17 . The device of  claim 16  wherein the processor is further configured to determine a set of spatial weights based on a set of neighboring pixels, and is further configured to filter the pixel intensity of the current frame based on the determined intensity weight and the set of determined spatial weights. 
     
     
         18 . The device of  claim 16  wherein the filtering parameter is a temporal filtering parameter and the processor is further configured to determine the temporal filtering parameter based on a set of residue images. 
     
     
         19 . The device of  claim 16  wherein the processor is further configured to determine the filtering parameter based on a spatial statistical representation of pixel intensity. 
     
     
         20 . The device of  claim 19  wherein the filtering parameter is based on a variance of image intensity within a region associated with the current pixel.