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Proceedings Paper

Image model: new perspective for image processing and computer vision
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Paper Abstract

We propose a new image model in which the image support and image quantities are modeled using algebraic topology concepts. The image support is viewed as a collection of chains encoding combination of pixels grouped by dimension and linking different dimensions with the boundary operators. Image quantities are encoded using the notion of cochain which associates values for pixels of given dimension that can be scalar, vector, or tensor depending on the problem that is considered. This allows obtaining algebraic equations directly from the physical laws. The coboundary and codual operators, which are generic operations on cochains allow to formulate the classical differential operators as applied for field functions and differential forms in both global and local forms. This image model makes the association between the image support and the image quantities explicit which results in several advantages: it allows the derivation of efficient algorithms that operate in any dimension and the unification of mathematics and physics to solve classical problems in image processing and computer vision. We show the effectiveness of this model by considering the isotropic diffusion.

Paper Details

Date Published: 21 May 2004
PDF: 11 pages
Proc. SPIE 5299, Computational Imaging II, (21 May 2004); doi: 10.1117/12.527132
Show Author Affiliations
Djemel Ziou, Univ. de Sherbrooke (Canada)
Madjid Allili, Bishop's Univ. (Canada)

Published in SPIE Proceedings Vol. 5299:
Computational Imaging II
Charles A. Bouman; Eric L. Miller, Editor(s)

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