Constrained PDF based histogram equalization for image constrast enhancement

Abstract

Histogram Equalization (HE) has proved to be a simple image contrast enhancement technique. However, it tends to change the mean brightness of the image to the middle level of the gray level range. In this paper, a smart contrast enhancement technique based on conventional HE algorithm is proposed. This Constrained PDF based Histogram Equalization (CPHE) technique takes control over the effect of traditional HE so that it performs the enhancement of an image without making any loss of details in it. In the proposed method, the probability distribution function (histogram) of an image is modified by introducing constraints before the histogram equalization (HE) is performed. This shows that such an approach provides a convenient and effective mechanism to control the enhancement process, while being adaptive to various types of images. Experimental results are presented and compared with results from other contemporary methods.