IMAGE ENHANCEMENT USING ENTROPY MAXIMIZATION

Abstract

Image enhancement is one of the most interesting domain of image processing. One of the techniques of image enhancement is contrast enhancement. Contrast enhancement in image processing is a very important technique. One of the most vastly used techniques for contrast enhancement is histogram equalization. It enhances the contrast of the input image by mapping the intensity levels based on the input probability distribution function of the image. HE finds application in many fields like medical image processing. HE, in general flats the histogram of the image and thus enhances the contrast of the input image. HE the results in the stretching of dynamic range. Although HE has low computational cost and has high performance, it is rarely used in electronic appliances as its straight use changes the original brightness of the image and hence result in distorted image. Histogram equalized image may also result in annoying artifacts and noise. Hence many techniques for contrast enhancement were developed in order to overcome the defects of HE. These include Bi-histogram brightness preserving histogram (BBHE), Dualistic sub image brightness preserving histogram(DSIH), Minimum mean brightness error bi-histogram equalization(MMBEBHE), Recursive Mean Separate Histogram Equalization(RMSHE),Entropy maximization histogram modification technique(EMHM)etc. The proposed algorithm show better results as compared to other algorithm.