East Asian J. Appl. Math., 11 (2021), pp. 788-807.
Published online: 2021-08
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An efficient feature-preserving fractional image denoising algorithm based on a nonlinear spatial-fractional anisotropic diffusion equation is proposed. Two-sided Grünwald-Letnikov fractional derivatives used in the PDE model are suitable to depict the local self-similarity of images. The short memory principle is employed to simplify the approximation scheme. Experimental results show that the method has an extremely high structural retention property and keeps a remarkable balance between noise removal and feature preserving.
}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.081220.270421}, url = {http://global-sci.org/intro/article_detail/eajam/19372.html} }An efficient feature-preserving fractional image denoising algorithm based on a nonlinear spatial-fractional anisotropic diffusion equation is proposed. Two-sided Grünwald-Letnikov fractional derivatives used in the PDE model are suitable to depict the local self-similarity of images. The short memory principle is employed to simplify the approximation scheme. Experimental results show that the method has an extremely high structural retention property and keeps a remarkable balance between noise removal and feature preserving.