Volume 38, Issue 3
Image Denoising via Time-Delay Regularization Coupled Nonlinear Diffusion Equations

J. Comp. Math., 38 (2020), pp. 417-436.

Published online: 2020-03

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• Abstract

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.

65N06, 65B99

qtma@nuist.edu.cn (Qianting Ma)

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@Article{JCM-38-417, author = {Ma , Qianting}, title = {Image Denoising via Time-Delay Regularization Coupled Nonlinear Diffusion Equations}, journal = {Journal of Computational Mathematics}, year = {2020}, volume = {38}, number = {3}, pages = {417--436}, abstract = {

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.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1811-m2016-0763}, url = {http://global-sci.org/intro/article_detail/jcm/15793.html} }
TY - JOUR T1 - Image Denoising via Time-Delay Regularization Coupled Nonlinear Diffusion Equations AU - Ma , Qianting JO - Journal of Computational Mathematics VL - 3 SP - 417 EP - 436 PY - 2020 DA - 2020/03 SN - 38 DO - http://doi.org/10.4208/jcm.1811-m2016-0763 UR - https://global-sci.org/intro/article_detail/jcm/15793.html KW - Image denoising, Galerkin's method, Existence, Uniqueness. AB -

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.

Qianting Ma. (2020). Image Denoising via Time-Delay Regularization Coupled Nonlinear Diffusion Equations. Journal of Computational Mathematics. 38 (3). 417-436. doi:10.4208/jcm.1811-m2016-0763
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