基于小波分析图像去噪的应用与实现  

Application and implementation of image denoising based on wavelet analysis

作　　者：王书源[1] 韩璐[1] 刘白冰 于巧娜 高佳[1] 

机构地区：[1]山东科技大学电气与自动化工程学院

出　　处：《电子世界》2015年第15期177-179,共3页Electronics World

摘　　要：针对图像使用的广度和深度,图像的消噪处理尤为重要,现有多种图像去噪方法。对比以傅里叶分析为基础的图像去噪方法数学方法,提出小波分析图像去噪处理方法。继承傅里叶去噪的优点,解决其时间窗和频率窗的乘积满足测不准关系的缺点。同时小波分析具有基函数不唯一的特点,可以选择更为适合的函数,对图像进行处理,达到消噪的效果,简化图像去噪的复杂程度。小波分析去噪分为图像的分解、消噪、重组三个部分。以MATLAB为实现平台,可以通过M文件编写和小波分析工具箱两种方式实现图像消噪。通过文中图片消噪结果的对比表明,小波分析可以较好的实现图像的去噪。并且实现方式多样化、过程简单化、处理灵活化。In view of the width and depth of the image,image denoising is extremely important and there are many methods of image denoising. Contrasted with Mathematical method of denoising,based on Fu Liye analysis,the method of wavelet analysis is put forward. Holding the advantages of Fu Liye＇s de noise,the product of the time window and frequency window to meet the uncertainty of the measurement uncertainty is solved. At the same time,wavelet analysis has the characteristic that the basis function is not unique,which can choose a more suitable function,process the image,achieve the effect of noise and simplify the complexity of the image denoising. Wavelet analysis denoising is divided into three parts, which are image decomposition,noise elimination and restructuring. With MATLAB as the platform,we can realize the image denoising by two ways,which are using M file and wavelet analysis toolbox. Through the comparison of the results of image denoising,wavelet analysis can better realize the image denoising. The realization way is various,the process is simple,and the process treatment activate.

关 键 词：小波分析 图像去噪 

分 类 号：TN911.73[电子电信—通信与信息系统]