A nonlinear image contrast sharpening approach based on Munsell's scale

Contrast is a measure of the variation in intensity or gray value in a specified region of an image. The region can be most or all of the image, giving rise to a global concept of contrast. The region might, on the other hand, be a small window in which case the concept of contrast is a locally defined expression. In this work, we introduce a nonlinear local contrast enhancement method. This method utilizes the Munsell value scale which is based upon human visual perception. Use of the Munsell value scale allows for the partitioning of the gray scale into ten discrete subintervals. Subsequent local processing occurs within each of these subintervals. Inside each subinterval, this method constructs a contrast enhancement function that is a smooth approximation to the threshold step function and which maps a given subinterval into itself. This function then thresholds the gray values in a subinterval in a smooth manner about a locally computed quantity called the mean edge gray value. By enhancing the contrast in this way, the original shades of gray are preserved. That is, the groupings of the gray values by subinterval are preserved. As a result, no gray value distortion is introduced into the image.