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Proceedings Paper

A Multilevel-Multiresolution Technique For Computer Vision Via Renormalization Group Ideas
Author(s): Basilis Gidas
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Paper Abstract

A multilevel-multiresolution method for image processing tasks and computer vision in general, is presented. The method is based on a combination of probabilistic models, Monte Carlo type algorithms, and renormalization group ideas. The method is suitable for implementation on massively parallel computers. It also yields a new global optimization algorithm potentially applicable to any cost function, but especially efficient for problems which are governed by local spatial relations.

Paper Details

Date Published: 20 April 1988
PDF: 5 pages
Proc. SPIE 0880, High Speed Computing, (20 April 1988); doi: 10.1117/12.944054
Show Author Affiliations
Basilis Gidas, Brown University (United States)


Published in SPIE Proceedings Vol. 0880:
High Speed Computing
David P. Casasent, Editor(s)

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