Comparative Study and Implementation of Image Enhancement Techniques based on Histogram Equalization

Histogram equalization (HE) is one of the common methods used for image enhancement. Histogram equalization has proved to be a simple and effective image contrast enhancement technique. The major difference among the methods in this family is the criteria used to divide the input histogram. For preserving the input brightness of the image, there is a segment to avoid the generation of non-existing artifacts in the output image. Although these methods preserve the input brightness on the output image with a significant contrast enhancement, they may produce images with do not look as natural as the input ones. The basic idea of HE method is to re-map the gray levels of an image. HE tends to introduce some annoying artifacts and unnatural enhancement. To overcome these drawbacks different brightness preserving techniques are used for image enhancement. In this paper, four different types of histogram modification methods i.e. CHE,CLAHE, BBPHE & BPDFHE are implemented in MATLAB. The performance of these techniques is then compared using various parameters such as Peak signal to noise ratio (PSNR), Mean squared error (MSE), Signal to noise ratio (SNR), Absolute mean brightness error(AMBE) and Entropy. Theresults show that BPDFHE technique is the most efficient technique for image enhancement among compared techniques. Keywords— Contrast enhancement, Histogram equalization brightness preserving, Background Brightness Preserving,histogram partition