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

被引：98

作者：

Guo, Zhichang ^{[1
]}

Sun, Jiebao ^{[1
]}

Zhang, Dazhi ^{[1
]}

Wu, Boying ^{[1
]}

机构：

[1] Harbin Inst Technol, Dept Math, Harbin 150001, Peoples R China

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2012年 / 21卷 / 03期

关键词：

Diffusion mode; edge indicator; forward and backward diffusion; Perona-Malik (PM) equation; variable exponent; EDGE-DETECTION; ANISOTROPIC DIFFUSION; NONLINEAR DIFFUSION; COMMON FRAMEWORK; EFFICIENT;

D O I：

10.1109/TIP.2011.2169272

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：958 / 967

页数：10

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