An adaptive diffusion coefficient selection for image denoising

被引:44
|
作者
Rafsanjani, Hossein Khodabalchshi [1 ]
Sedaaghi, Mohammad Hossein [1 ]
Saryazdi, Saeid [2 ]
机构
[1] Sahand Univ Technol, Dept Elect Engn, POB 513351996, Tabriz, Iran
[2] Shahid Bahonar Univ Kerman, Dept Elect Engn, POB 76169133, Kerman, Iran
关键词
Image denoising; Diffusion coefficient; PDE; Texture; Edge; PERONA-MALIK MODEL; ANISOTROPIC DIFFUSION; BACKWARD DIFFUSION; NOISE; ENHANCEMENT; EQUATION; DOMAIN; FILTER;
D O I
10.1016/j.dsp.2017.02.004
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
In the gradient dependent denoising methods based on partial differential equation, the process of denoising is controlled through the gradient operation. Hence, the edges are preserved while texture and fine details (having oscillatory nature, the same as noise) are degraded. This paper proposes an algorithm which adaptively selects diffusion coefficient using the residual local power and the amount of the gradient magnitude. Since texture regions correspond to large values of the local power of the residue, this strategy permits to simultaneously preserve the edges, textures, and fine details. To evaluate the proposed method, a variety of experiments are carried out confirming the performance of the proposed algorithm with respect to peak signal-to-noise ratio, mean structural similarity, universal quality index, visual information fidelity and visual quality. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:71 / 82
页数:12
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