Comparative analysis of different methods for image enhancement

Abstract

Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima (WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean (µ), standard deviation (σ), mean square error (MSE) and PSNR (peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement.

Keywords

image enhancement / wavelet transform / histogram equalization / unsharp masking (UM) / modulus maxl mum / threshold

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