基于小波变换的图像降噪技术  

Research of Image Noise Reduction Based on Wavelet Transform

作　　者：孙东宁[1] 张丽[2] 闫朝文[1] SUN Dong-ning, ZHANG Li, YAN Chao-wen （1.Shool of Information and Engineering Shanghai Maritime University, Shanghai 200135, China; 2.Institute of Marine Material Science ＆ Engineering, Shanghai Maritime University, Shanghai 200135, China）

机构地区：[1]上海海事大学信息工程学院,上海200135 [2]上海海事大学海洋材料科学与工程研究院,上海200135

出　　处：《电脑知识与技术》2010年第01X期691-692,共2页Computer Knowledge and Technology

摘　　要：小坡变换在图像处理中有着重要的应用，在基于小波的图像降噪处理算法中，常常存在着对图像信息的过分滤除和对噪声信息的欠滤出，而使得对图像降噪后不仅没有提高信噪比反而使其降低了，这就不利于对图像进行分析观察。究其原因主要是由于阈值选取和处理方法不恰当引起的。在小波空间Donoho闺值算法的基础上，结合Birge—Massart策略得出的多层阂值图像降噪处理算法，从而达到较好的保留图像的细节有用信息、降低噪声的目的，仿真实验表明对一般受低噪声干扰的图像做降噪处理时，效果较好。Wavelet transform in image processing has important applications, in the image denoising which based on wavelet processing algorithrns, it is often to over-filtered image information and the noise doesn＇t filter out enough, causing not only failed to post the image noise Instead, but also lowered to improve signal to noise ratio, which is not conducive to observation and analysis of the image.This mainly due to threshold selection and processing methods are not appropriate. In the wavelet space Donoho threshold algorithm based on the Birge-Massart strategy with resulting noise reduction mnlti-threshold image processing algorithms to achieve the better to retain the image details of useful information and reduce noise, simulation restflts Show that the effect is good when image is noised by the low-noise.

关 键 词：小波变换 图像降噪 阈值 

分 类 号：TP18[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]