EE4206/EE5806 Digital Image Processing: tut#6 Q1. answer -- Local histogram processing
The idea is to devise transformation functions based on the intensity distribution in a neighborhood of every pixel in the image.
1. The procedure is to define a neighborhood and MOVE its CENTRE from pixel to pixel.
2. At EACH location, the histogram of the points in the neighborhood is computed and either a histogram equalization or histogram specification transformation function is obtained.
3. This function is used to MAP the intensity of the pixel CENTERED in the neighborhood.
4. The center of the neighborhood region is then MOVED to an ADJACENT pixel location and the procedure is repeated.
5. * Because ONLY ONE row or column of the neighborhood changes during a pixel-to-pixel translation of the neighborhood, updating the histogram obtained in the previous location with the NEW data introduced at EACH motion step is possible.
6. This approach has obvious advantages over repeatedly computing the histogram of ALL pixels in the neighborhood region each time the region is moved one pixel location.