Contrast Enhancement in Gray Level Images

Abstract

Contrast enhancement is a very important step in image processing, pattern recognition and computer vision .Histogram Equalization (HE) is widely used for contrast Enhancement . This paper discussed five techniques of contrast enhancement, i.e. Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Brightness preserving Bi_Histogram Equalization (BBHE), Dualistic Sub_Image Histogram Equalization (DSIHE) and Recursive Sub_Image Histogram equalization (RSIHE). Also it presented the comparison among the various techniques that show the image enhances the overall contrast and visibility of local details, by using two measures: Peak-Signal-to-Noise-Ratio (PSNR) and Absolute Mean Brightness Error (AMBE) to check the signal and brightness power respectively. This work is programmed by MATLAB VER.7.8.