Study on the Wavelet Threshold Noise Reduction Technique Based on MATLAB

Abstract

In the process of image processing, image acquisition, conversion and transmission are often affected by imaging equipment and external environmental noise impact, so that the image degradation. The follow-up image processing of digital image noise influence is bigger, so there are very important realistic meanings to remove image noise. Image denoising is an extensive image pretreatment technology, the purpose is to improve the image SNR, highlight the expectations of the image features. Modern image noise reduction technology is very much, and each has its advantages and disadvantages, in the process of image processing, image acquisition, conversion and transmission are often affected by imaging equipment and external environmental noise impact, so that the image degradation. The follow-up image processing of digital image noise influence is bigger, so there are very important realistic meanings to remove image noise. Image denoising is an extensive image pretreatment technology, the purpose is to improve the image SNR, highlight the expectations of the image features. Modern image noise reduction technology is very much, and each has its advantages and disadvantages, among them, wavelet threshold denoising is a denoising technique can have good treatment of Gauss noise, wavelet threshold denoising is divided into soft threshold and hard threshold denoising, for different noise, can take different threshold denoising, can get very good the effect of. MATLAB is a very good software, and her language is simple and powerful, can finish all kinds of simulation of signal processing, especially the simulation of image denoising. Among them, wavelet threshold denoising is a denoising technique can have good treatment of Gauss noise, wavelet threshold denoising is divided into soft threshold and hard threshold denoising, for different noise, can take different threshold denoising, can get very good effect. MATLAB is a very good software, and her language is simple and powerful, can finish all kinds of simulation of signal processing, especially the simulation of image denoising.