A Novel Image Denoising Algorithm Based on Non-subsampled Contourlet Transform and Modified NLM

被引:0
|
作者
Yang, Huayong [1 ]
Lin, Xiaoli [1 ,2 ]
机构
[1] Wuhan Univ Sci & Technol, City Coll, Dept Informat Engn, Wuhan 430083, Hubei, Peoples R China
[2] Wuhan Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430065, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Non-subsampled contourlet transform (NSCT); Non-local mean (NLM); Denoising;
D O I
10.1007/978-3-319-95957-3_71
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A novel image denoising algorithm based on non-subsampled contourlet transform (NSCT) and modified non-local mean (NLM) is proposed. First, we utilize NSCT to decompose the images to obtain the high frequency coefficients. Second, the high frequency coefficients are used for modified NLM denoising. Finally, the NLM weight values are calculated by modified bisquare function instead of Gaussian kernel function of the traditional NLM, and each noise coefficient is corrected to get the denoised image. According to results of the simulation experiment, the denoising results of the proposed algorithm obtain higher peak signal-to-noise ratio (PSNR) and better retains structural information of image in subjective vision.
引用
收藏
页码:689 / 699
页数:11
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