Research on adaptive image denoising based on wavelet transform

被引：0

作者：

Wang, NL ^{[1
]}

Han, P ^{[1
]}

Wang, DF ^{[1
]}

机构：

[1] N China Elect Power Univ, Dept Automat, Baoding 071003, Peoples R China

来源：

PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年

关键词：

image denoising; wavelet transform; shrinkage function; anisotropic diffusion equation;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An effective method based on wavelet transform is introduced in this paper for image denoising without blurring the useful edge information. Wavelet shrinkage at consecutive scales are utilized on the sub-images exerted wavelet decomposition, meanwhile a statistical model is referenced to determine the proper shrinkage functions and threshold for discriminate the edge information from that of noise. Finally, anisotropic diffusion equation is applied to the modified wavelet coefficients to preserve edges information that is not isolated. This method is of adaptability to different amounts of noise in the image, and robustness to larger noise contamination. Simulation results present a superior performance in the aspect of image denoising.

引用

页码：4352 / 4355

页数：4

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