Wiener filter-based wavelet domain denoising

被引:13
|
作者
Wang, Jin [1 ,2 ]
Wu, Jiaji [3 ]
Wu, Zhensen [1 ]
Jeong, Jechang [2 ]
Jeon, Gwanggil [3 ,4 ]
机构
[1] Xidian Univ, Sch Phys & Optoelect Engn, Xian, Shaanxi, Peoples R China
[2] Hanyang Univ, Dept Elect & Comp Engn, Seoul, South Korea
[3] Xidian Univ, Sch Elect Engn, Xian, Shaanxi, Peoples R China
[4] Incheon Natl Univ, Dept Embedded Syst Engn, Incheon, South Korea
基金
中国国家自然科学基金;
关键词
Wiener filter; Image denoising; High resolution estimation; BIVARIATE SHRINKAGE;
D O I
10.1016/j.displa.2016.12.003
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The wavelet domain Wiener filter has been widely adopted as an effective image denoising method that has low complexity. In this paper we propose a novel Wiener filter with high-resolution estimation that determines the signal power while preserving the edge information. We assume that a noisy image is composed of noise and the original image, which are mutually orthogonal. Based on this assumption, we utilize the local covariance to obtain high-resolution coefficients from the low-resolution coefficients and to estimate the signal variance in the Wiener filter by using the high resolution values. The experimental results show that the proposed algorithm improves the objective and subjective performance significantly. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:37 / 41
页数:5
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