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

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.