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Proceedings Paper

Sampling conditions for anisotropic diffusion
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Paper Abstract

Multi-resolution image analysis utilizes subsampled image representations for applications such as image coding, hierarchical image segmentation and fast image smoothing. An anti-aliasing filter may be used to insure that the sampled signals adequately represent the frequency components/features of the higher resolution signal. Sampling theories associated with linear anti-aliasing filtering are well-defined and conditions for nonlinear filters are emerging. This paper analyzes sampling conditions associated with anisotropic diffusion, an adaptive nonlinear filter implemented by partial differential equations (PDEs). Sampling criteria will be defined within the context of edge causality, and conditions will be prescribed that guarantee removal of all features unsupported in the sample domain. Initially, sampling definitions will utilize a simple, piecewise linear approximation of the anisotropic diffusion mechanism. Results will then demonstrate the viability of the sampling approach through the computation of reconstruction errors. Extension to more practical diffusion operators will also be considered.

Paper Details

Date Published: 28 December 1998
PDF: 12 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334658
Show Author Affiliations
C. Andrew Segall, Northwestern Univ. (United States)
Scott Thomas Acton, Oklahoma State Univ. (United States)
Aggelos K. Katsaggelos, Northwestern Univ. (United States)

Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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