Image denoising using local Wiener filter and its method noise

被引:31
|
作者
Zhang, Xiaobo [1 ]
机构
[1] Xianyang Normal Univ, Inst Graph & Image Proc, Xianyang 712000, Peoples R China
来源
OPTIK | 2016年 / 127卷 / 17期
基金
中国国家自然科学基金;
关键词
Image denoising; Local Wiener filter; SURE-LET; NSST; WAVELET; ALGORITHM;
D O I
10.1016/j.ijleo.2016.05.002
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper proposed a new image denoising method on local Wiener filter. Firstly, non-subsampled shearlet transform (NSST) is used to decompose noisy image since NSST is an effective multi-scale and multi-direction analysis tool in image processing. And then the high frequency NSST coefficients are denoised by a shrinkage function based on local Wiener filter. In this new shrinkage function, the method noise of local Wiener filter is employed effectively by using the Stein's unbiased risk estimate and linear expansion of thresholds (SURE-LET) strategy. Finally, the inverse NSST is used to obtain the denoised image. Experimental results show that the proposed method is very good in performance compared to the state-of-the-art wavelet-based algorithms. (C) 2016 Elsevier GmbH. All rights reserved.
引用
收藏
页码:6821 / 6828
页数:8
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