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Proceedings Paper

Adaptive nonlinear diffusion algorithm for image filtering
Author(s): Yung Wang; Jesse S. Jin; John B. Hiller
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Paper Abstract

The nonlinear anisotropic diffusive process has shown the good property of eliminating noise while preserving the accuracy of edges, and has been widely used in image processing. However, filtering depends on the threshold of the diffusion process, i.e., the cut-off contrast of edges. The threshold varies form image to image and even from region to region within an image. The problem compounds with intensity distortion and contrast variation. We have developed an adaptive diffusion scheme by applying the Central Limit Theorem to selecting the threshold. Gaussian distribution and Rayleigh distribution are used to estimate the distributions of visual objects in images. Regression under such distributions separates the distribution of the major object from other visual objects in a single peak histogram. The separation helps to automatically determine the threshold. A fast algorithm is derived for the regression process. The method has been successfully used in filtering various medical images.

Paper Details

Date Published: 3 April 1997
PDF: 12 pages
Proc. SPIE 3028, Real-Time Imaging II, (3 April 1997); doi: 10.1117/12.270348
Show Author Affiliations
Yung Wang, Univ. of New South Wales (Australia)
Jesse S. Jin, Univ. of New South Wales (Australia)
John B. Hiller, Univ. of New South Wales (Australia)


Published in SPIE Proceedings Vol. 3028:
Real-Time Imaging II
Divyendu Sinha, Editor(s)

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