Perception-based contrast enhancement of images

Study of contrast sensitivity of the human eye shows that our suprathreshold contrast sensitivity follows the Weber Law and, hence, increases proportionally with the increase in the mean local luminance. In this paper, we effectively apply this fact to design a contrast-enhancement method for images that improves the local image contrast by controlling the local image gradient with a single parameter. Unlike previous methods, we achieve this without explicit segmentation of the image, either in the spatial (multiscale) or frequency (multiresolution) domain. We pose the contrast enhancement as an optimization problem that maximizes the average local contrast of an image strictly constrained by a perceptual constraint derived directly from the Weber Law. We then propose a greedy heuristic, controlled by a single parameter, to approximate this optimization problem.