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

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 te...

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Bibliographic Details
Published in:IEEE transactions on image processing 2012-03, Vol.21 (3), p.958-967
Main Authors: Guo, Zhichang, Sun, Jiebao, Zhang, Dazhi, Wu, Boying
Format: Article
Language:English
Subjects:
Adaptation models
Algorithms
Applied sciences
Detection, estimation, filtering, equalization, prediction
Diffusion
Diffusion mode
Edge detection
edge indicator
Equations
Exact sciences and technology
Exponents
forward and backward diffusion
Heating
Image edge detection
Image processing
Information, signal and communications theory
Mathematical analysis
Mathematical model
Mathematical models
Noise
Pattern recognition
Perona-Malik (PM) equation
Signal and communications theory
Signal processing
Signal, noise
Smoothing methods
Telecommunications and information theory
variable exponent
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Summary: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.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2011.2169272