Image Denoising Method Based On Wavelet Transform

Along with the increasing popularity of computer in the information age,the quality desire of digital image becomes more and more strict.But digital image is usually corrupted by the noise in its acquisition or transmission.This is inconsistent with people's visual effects,and is not conducive to the further image processing.Therefore,the image denoising has a strong theoretical significance and applied value.We mainly study image denoising methods based on wavelet transform in this article.Several results are obtained from the research of the image denoising.The paper is organized as follows:In Chapter 1,we outline the development of wavelet analysis,image denoising methods and the necessity of the wavelet image denoising.In Chapter 2,the fundamental theories of wavelet analysis are discussed in detail,we introduce the theories which include wavelet transform,multi-resolution analysis,wavelet functions and wavelet transform of image.The contents of the chapter are the theoretical basis of wavelet image denoising.In Chapter 3,we investigate the methods of wavelet threshold denoising and wavelet packet denoising.First,the evaluation criteria of quality of wavelet image denoising are introduced. Second,the methods of wavelet threshold denoising and wavelet packet denoising are discussed.Finally,the experiments show the effects of the denoising methods and come to the conclusions.In Chapter 4,We introduce an improved threshold function in the basis of discussing the selections of the wavelet functions and threshold functions.By way of examples,we study the different performance of image denoising by making use of different wavelet functions and threshold functions,and drop the conclusions.In Chapter 5,a wavelet image denoising based on adaptive threshold is proposed to overcome the limitations of the traditional methods for image denoising.The experimental results show that the image denoising method is efficient and practical.