@Article{EAJAM-11-4,
author = {Xu, Maoyuan and Xie, Xiaoping},
title = {An Efficient Feature-Preserving Image Denoising Algorithm Based on a Spatial-Fractional Anisotropic Diffusion Equation},
journal = {East Asian Journal on Applied Mathematics},
year = {2021},
volume = {11},
number = {4},
pages = {788--807},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.081220.270421},
url = {https://global-sci.com/article/82537/an-efficient-feature-preserving-image-denoising-algorithm-based-on-a-spatial-fractional-anisotropic-diffusion-equation}
}