Wavelet-based Image Thresholding Denoising Method

With internet and computer are used more and moretoday, the multimedia just like audio, video etc. enriches human's life a lot. Meanwhile, the requirement of image quality is raising day by day. Therefore, it is necessary to do some research on image processing.Digital image is usually corrupted by the noise in its acquisition or transmission, which degrades the quality of the original image. In order to solve this problem and gain clearer images, many kinds of image denoising approaches areproposed. Wavelet image denoising has been well acknowledged as an important image denoising method for its splendid characteristics. Especially wavelet thresholding denoising method because of its simple principle and excellent performance, researchers have paid much more attention to it in the recent years.Based on the profound comprehension and generalization of a lot of existing literature on wavelet denoising, some disadvantages in the current approaches are analyzed. The structure of the thesis is the following. First, the theory and characteristicsof wavelet transform are generalized; second, the applications in the area of image denoising are described; third, the wavelet image denoising methods are classified and introduced, moreover, the shortcomings of thresholding denoising method are specially analyzed; in the end, after analyzing and comparing the classical thresholding denoising methods, a new threshold selecting method and a new t hresholding function are proposed.Simulation experiments are implemented by MATLAB7.0 wavelet toolbox. And experiment results shows that the new methods usually obtain better performance than classical thresholding denoising methods.