Contrast enhancement in gray level images

Abstract EN

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.