Enhancement of medical images using a fuzzy model for segment dependent local equalization

A novel model for fuzzy equalization of medical images is proposed. The method requires a preprocessing step which accomplishes a fuzzy segmentation of the image into N segments with overlapping fuzzy boundaries. Histogram equalization is performed according to individual equalization functions derived from each segment of the image. A fuzzy membership function is associated with each segment. Enhancement results compare well against histogram equalization techniques that derive the equalization transform function from the global histogram of the image.