Nonlinear Anisotropic Diffusion Using Adaptive Weighted Median Filters 


Vol. 32,  No. 5, pp. 542-549, May  2007


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  Abstract

Recently, many research activities in the image processing area are concentrated on developing new algorithms by finding the solution of the 'diffusion equation'. The diffusion algorithms are expected to be utilized in numerous applications including noise removal and image restoration, edge detection, segmentation, etc. In this paper, at first, it will be shown that the anisotropic diffusion algorithms have the similar structure with the adaptive FIR filters with cross-shaped 5-tap kernel, and this relatively small-sized kernel causes many iterating procedure for satisfactory filtering effects. Moreover, it will also be shown that lots of modifications which are adopted to the conventional Gaussian diffusion method in order to weaken the edge blurring nature of the linear filtering process increases another computational burden. We propose a new Median diffusion scheme by replacing the adaptive linear filters in the diffusion process with the AWM (Adaptive Weighted Median) filters. A diffusion-equation-based adaptation scheme is also proposed. With the proposed scheme, the size of the diffusion kernel can be increased, and thus diffusion speed greatly increases. Simulation results shows that the proposed Median diffusion scheme outperforms in noise removal (especially impulsive noise), and edge preservation.

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  Cite this article

[IEEE Style]

I. Hwang, K. Lee, W. Kim, "Nonlinear Anisotropic Diffusion Using Adaptive Weighted Median Filters," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 5, pp. 542-549, 2007. DOI: .

[ACM Style]

In-Ho Hwang, Kyung-Hoon Lee, and Woong-Hee Kim. 2007. Nonlinear Anisotropic Diffusion Using Adaptive Weighted Median Filters. The Journal of Korean Institute of Communications and Information Sciences, 32, 5, (2007), 542-549. DOI: .

[KICS Style]

In-Ho Hwang, Kyung-Hoon Lee, Woong-Hee Kim, "Nonlinear Anisotropic Diffusion Using Adaptive Weighted Median Filters," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 5, pp. 542-549, 5. 2007.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880