Modified BM3D algorithm for image denoising using nonlocal centralization prior

被引:31
|
作者
Zhong, Hua [1 ]
Ma, Ke [1 ]
Zhou, Yang [1 ]
机构
[1] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Int Res Ctr Intelligent Percept & Computat, Minist Educ, Xian 710071, Shaanxi Provinc, Peoples R China
基金
中国国家自然科学基金;
关键词
Denoising; Wavelet; Shrinkage; Block matching; Nonlocal; Sparsity; WAVELET SHRINKAGE; DOMAIN;
D O I
10.1016/j.sigpro.2014.08.014
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Block matching and 3D collaborative filtering (BM3D) has shown great power for image denoising. For grouped image blocks, this letter proposes to remove the 1D transform inter-blocks and introduce the nonlocal centralization prior to better utilize both local sparsity of wavelet coefficients and nonlocal similarity of grouped blocks. Three nonlocal shrinkage functions are developed under different norm restrictions of wavelet coefficients intra- and inter-blocks. Such shrinkage functions are verified to be competitive or better than the BM3D algorithm and other state-of-the-art denoising methods. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:342 / 347
页数:6
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