An Efficient Feature-Preserving Image Denoising Algorithm Based on a Spatial-Fractional Anisotropic Diffusion Equation

An Efficient Feature-Preserving Image Denoising Algorithm Based on a Spatial-Fractional Anisotropic Diffusion Equation

Year:    2021

Author:    Maoyuan Xu, Xiaoping Xie

East Asian Journal on Applied Mathematics, Vol. 11 (2021), Iss. 4 : pp. 788–807

Abstract

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.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/eajam.081220.270421

East Asian Journal on Applied Mathematics, Vol. 11 (2021), Iss. 4 : pp. 788–807

Published online:    2021-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    20

Keywords:    Image denoising feature preserving spatial-fractional diffusion equation two-sided derivative Grünwald-Letnikov derivative

Author Details

Maoyuan Xu

Xiaoping Xie

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