IMAGE DENOISING VIA TIME-DELAY REGULARIZATION COUPLED NONLINEAR DIFFUSION EQUATIONS

被引:2
作者
Ma, Qianting [1 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Nanjing, Peoples R China
关键词
Image denoising; Galerkin's method; Existence; Uniqueness; EDGE-DETECTION; MINIMIZATION; MODEL;
D O I
10.4208/jcm.1811-m2016-0763
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A novel nonlinear anisotropic diffusion model is proposed for image denoising which can be viewed as a novel regularized model that preserves the cherished features of Perona-Malik to some extent. It is characterized by a local dependence in the diffusivity which manifests itself through the presence of p(x)-Laplacian and time-delay regularization. The proposed model offers a new nonlinear anisotropic diffusion which makes it possible to effectively enhance the denoising capability and preserve the details while avoiding artifacts. Accordingly, the restored image is very clear and becomes more distinguishable. By Galerkin's method, we establish the well-posedness in the weak setting. Numerical experiments illustrate that the proposed model appears to be overwhelmingly competitive in restoring the images corrupted by Gaussian noise.
引用
收藏
页码:417 / 436
页数:20
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