Mammographic image enhancement and denoising based on redundant wavelet transform

In this paper, we develop a new approach to mammographic image enhancement and denoising based on redundant wavelet transform. The first part deals with the method of mammographic enhancement. Firstly, we enhance the image using a fast and effective enhancement method by the local standard deviation values, and stretch/compress factitiously the gray interval between neighbor pixel for different gray value according to the human visual curve in Figure 1 considering the character of the human visual system, so as to distribute the redundant gray of some gray value to eye to the wanting fields. The method boosts up the local regions to different degrees rationally. The second part deals with the multiscale image processing for image denosing. The image is decomposed into several subbands by redundant wavelet transform, and then is reconstructed by different weights.