Diffusion scheme using mean filter and wavelet coefficient magnitude for image denoising

被引:6
作者
Zhang, Xiaobo [1 ]
Zhang, Shunli [2 ]
机构
[1] Xianyang Normal Univ, Inst Graph & Image Proc, Xianyang 712000, Peoples R China
[2] Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Peoples R China
基金
中国国家自然科学基金;
关键词
Image denoising; Mean filter; Local window; ANISOTROPIC DIFFUSION; WIENER FILTER; DOMAIN; SHRINKAGE;
D O I
10.1016/j.aeue.2016.04.012
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
A novel wavelet-domain diffusion scheme is proposed for image denoising. In the proposed scheme, the shrinkage function plays an important role for denoising performance. By researching the signal information extraction feature map of locally adaptive linear minimum mean square-error estimation (LALMMSE) method, the proposed shrinkage function is produced. In the design of the function, local mean filter is used to effectively extract noise-free wavelet coefficient information while original noisy wavelet coefficient magnitude is used to offset the negative effect produced by information extraction. Tests show that the proposed new method is always on par with or better than the state-of-the-art image denoising techniques in the wavelet domain. Furthermore, the proposed method is also very efficient compared to other methods. (C) 2016 Elsevier GmbH. All rights reserved.
引用
收藏
页码:944 / 952
页数:9
相关论文
共 16 条
[1]   The SURE-LET approach to image denoising [J].
Blu, Thierry ;
Luisier, Florian .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2007, 16 (11) :2778-2786
[2]   Adaptive wavelet thresholding for image denoising and compression [J].
Chang, SG ;
Yu, B ;
Vetterli, M .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2000, 9 (09) :1532-1546
[3]   IDEAL SPATIAL ADAPTATION BY WAVELET SHRINKAGE [J].
DONOHO, DL ;
JOHNSTONE, IM .
BIOMETRIKA, 1994, 81 (03) :425-455
[4]   Adapting to unknown smoothness via wavelet shrinkage [J].
Donoho, DL ;
Johnstone, IM .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1995, 90 (432) :1200-1224
[5]   Despeckling of ultrasound medical images using nonlinear adaptive anisotropic diffusion in nonsubsampled shearlet domain [J].
Gupta, Deep ;
Anand, R. S. ;
Tyagi, Barjeev .
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2014, 14 :55-65
[6]   A new SURE approach to image denoising: Interscale orthonormal wavelet thresholding [J].
Luisier, Florian ;
Blu, Thierry ;
Unser, Michael .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2007, 16 (03) :593-606
[7]  
Mandava AK, 2011, J ELECTRON IMAGING, V20
[8]   Low-complexity image denoising based on statistical modeling of wavelet coefficients [J].
Mihçak, MK ;
Kozintsev, I ;
Ramchandran, K ;
Moulin, P .
IEEE SIGNAL PROCESSING LETTERS, 1999, 6 (12) :300-303
[9]   Using diffusion equations for improving performance of wavelet-based image denoising techniques [J].
Nikpour, M. ;
Hassanpour, H. .
IET IMAGE PROCESSING, 2010, 4 (06) :452-462
[10]   Image denoising using scale mixtures of Gaussians in the wavelet domain [J].
Portilla, J ;
Strela, V ;
Wainwright, MJ ;
Simoncelli, EP .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2003, 12 (11) :1338-1351