Adaptive Perona–Malik Model Based on the Variable Exponent for Image Denoising

Authors:
Zhichang Guo;Jiebao Sun;Dazhi Zhang;Boying Wu
Affiliations:
Department of Mathematics, Harbin Institute of Technology, Harbin, China;Department of Mathematics, Harbin Institute of Technology, Harbin, China;Department of Mathematics, Harbin Institute of Technology, Harbin, China;Department of Mathematics, Harbin Institute of Technology, Harbin, China
Venue:
IEEE Transactions on Image Processing
Year:
2012

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Fast communication: Image denoising using modified Perona-Malik model based on directional Laplacian

Signal Processing

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Abstract

This paper introduces a class of adaptive Perona–Malik (PM) diffusion, which combines the PM equation with the heat equation. The PM equation provides a potential algorithm for image segmentation, noise removal, edge detection, and image enhancement. However, the defect of traditional PM model is tending to cause the staircase effect and create new features in the processed image. Utilizing the edge indicator as a variable exponent, we can adaptively control the diffusion mode, which alternates between PM diffusion and Gaussian smoothing in accordance with the image feature. Computer experiments indicate that the present algorithm is very efficient for edge detection and noise removal.