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基于多小波变换及多层阈值的图像降噪研究
引用本文:郑武,余胜生,周敬利,陈加忠.基于多小波变换及多层阈值的图像降噪研究[J].计算机工程与应用,2004,40(13):14-15,122.
作者姓名:郑武  余胜生  周敬利  陈加忠
作者单位:华中科技大学计算机学院,武汉,430074
基金项目:湖北省自然科学基金项目:启发式低比特率视频压缩和码率控制研究资助
摘    要:提出了一种基于多小波变换分层阈值的图像降噪的方法。此方法首先对一幅噪声图像进行多小波分解;接着根据多小波分解后的能量分布特性,在不同尺度的高频子带内,对小波系数进行不同阀值处理;最后经多小波反变换,得到重构图像。实验结果表明:此方法既可以有效地降低噪声,又可以较好地保持图像细节。

关 键 词:图像去噪  多小波变换  分层阈值
文章编号:1002-8331-(2004)13-0014-02

An Approach to Image Noise Reduction Based on Multiwavelet Transform and Multilevel Threshold
Zheng Wu,Yu,Shengsheng Zhou Jingli Chen Jiazhong.An Approach to Image Noise Reduction Based on Multiwavelet Transform and Multilevel Threshold[J].Computer Engineering and Applications,2004,40(13):14-15,122.
Authors:Zheng Wu  Yu  Shengsheng Zhou Jingli Chen Jiazhong
Abstract:A Method of image denoising based on multiwavelet transform and multilevel threshold is proposed.Firstly,noised image are decomposed by multiwavelet transform,Secondly,in high frequency area with different scale,the coefficients are dealed with different threshold according to coefficients energy distribution.Finally,reconstructed image can be obtained by using the inverse multiwavelet transform for all important coefficients and approximation coefficients.Experimental results prove that by using this method,image noise can be reduced effectively and image details can be preserved a lot.
Keywords:image denoising  multiwavelet transform  multilevel threshold  
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