Histogram Eualization Techniques for Image Enhancement using Fuzzy Logic

In image enhancement various enhancement schemes have been used for enhancing which includes gray scale manipulation, filtering and Histogram Equalization (HE). Histogram equalization techniques using fuzzy logic is one of the unique image enhancement technique. It became a popular technique for contrast enhancement because this method is simple and effective. In the latter case, preserving the input brightness of the image is required to avoid the generation of non-existing artifacts in the output image and image contrast is limited. Although these methods preserve and enhance the input brightness on the output image with a significant contrast enhancement and large varies in PSNR on the operation of image, they may produce images with do not look as natural as the input ones. The basic idea of 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 existing defined brightness preserving techniques are used to check their performance measurement which are covered in our research. Comparative analysis of different enhancement techniques will be carried out. This comparison will be done on the basis of subjective and objective parameters. Subjective parameters are visual quality and computation time and objective parameters are Peak signal to-noise ratio (PSNR), Contrast and Error.