Local Entropy-Based Coupled Anisotropic Diffusion for Detail-And Edge-Preserving Smoothing

Author:

Zhao De1ORCID,Chen Lan2ORCID

Affiliation:

1. College of Mathematics and Statistics, Chongqing University, Chongqing 401331, China

2. Children’s Hospital of Chongqing Medical University, Chongqing 401331, China

Abstract

It is important in image restoration to remove noise while preserving sharp edges and fine details such as blurred thin edges and low-contrast fine feature. The Perona–Malik (P-M) model is a well-known anisotropic diffusion denoising model, which can effectively remove noise while preserving edges. However, its diffusion coefficient only associates with the gradient of each pixel but not with the local region information; thus, the P-M model is not able to effectively preserve the important details of image. To address this problem, this paper proposes an anisotropic diffusion denoising model based on local entropy. The diffusion coefficient of the new model not only depends on the gradient of image but also on the local region information described by local entropy. On this basis, a coupled anisotropic diffusion scheme is proposed for detail-and edge-preserving smoothing. Experimental results show that the proposed model not only can effectively remove noise while preserving the boundaries better but also can maintain important details in an image very well.

Funder

Chongqing Technological Innovation and Application Development Project

Publisher

Hindawi Limited

Subject

Modeling and Simulation

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