Enhancement of Contrast and Resolution of Gray Scale and Color Images by Wavelet Decomposition and Histogram Shaping and Shifting

In this paper a new methodology of enhancement of images is well proposed. This method combines two very popular techniques of enhancement i.e. Wavelet decomposition and histogram shifting & shaping. In this we will use this method for enhancement of commercial images and natural images etc.. In this algorithm, a original image (gray scale and color image) is first decomposed in its discrete wavelet coefficients, then these wavelet coefficients filtered by global thresholding. This threshold value is calculated by histogram shifting & shaping method with the variable value of K coefficient. Inverse wavelet transform of filtered and modified wavelet coefficients of image give the reconstruction of original image. With this algorithm, a very new and efficient algorithm for reshaping of histogram that is capable in enhancing local details as well as properly preserving the image contrast, resolution and brightness is presented. In this paper, we show that a modified version of the measurement of enhancement by entropy (EME) can be used as an image similarity measure, and thus an image quality measure and calculated. Until now, EME has generally been used to measure the level of enhancement obtained using a given enhancement algorithm and enhancement parameter. In terms of EME values, this method of combination will gives better results.