外 文 文 献New method for image denoising while keeping edge information.doc

外 文 文 献 New method for image denoising while keeping edge information Edge information is the most important high- frequency information of an image, so we should try to maintain more edge information while denoising. In order to preserve image details as well as canceling image noise, we present a new image denoising method: image denoising based on edge detection. Before denoising, images edges are first detected, and then the noised image is divided into two parts: edge part and smooth part. We can therefore set high denoising threshold to smooth part of the image and low denoising threshold to edge part. The theoretical analyses and experimental results presented in this paper show that, compared to commonly-used wavelet threshold denoising methods, the proposed algorithm could not only keep edge information of an image, but also could improve signal-to-noise ratio of the denoised image. In the wavelet domain, the denoising algorithm based on the threshold filter is widely used, because it’s comparatively efficient and easy to realize. We can select a threshold according to the characteristic of the image, modifying all of thediscrete detail coefficients so as to reduce the noise. However, we are in the dilemma of determining the level of the threshold. The higher the threshold is, the bettereffectof denoising will be, and, at the same time, the blurrier the edge will be. The edges of an image mostly reflect the information of the image, and contain its basic character. According to research on human eyes, thecharacteristic of the edges is one of several characteristics that can strongly impress the visual system . Thus, when we process denoising, the first thing that we should care about is trying to retain edge information. This paper presents a new method for image denoising while keeping edge information. We first apply wavelet transform to a noised image, and then process edge detect