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Proceedings Paper

SAR imagery segmentation using probabilistic winner-take-all clustering
Author(s): Hossam M. Osman; Steven D. Blostein
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Paper Abstract

This paper applies a recently-developed neural clustering scheme, called 'probabilistic winner-take-all (PWTA)', to image segmentation. Experimental results are presented. These results show that the PWTA clustering scheme significantly outperforms the popular k-means algorithm when both are utilized to segment a synthetic-aperture-radar image representing ship targets in an open-ocean scene.

Paper Details

Date Published: 10 June 1996
PDF: 10 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242050
Show Author Affiliations
Hossam M. Osman, Queen's Univ. (Canada)
Steven D. Blostein, Queen's Univ. (Canada)


Published in SPIE Proceedings Vol. 2757:
Algorithms for Synthetic Aperture Radar Imagery III
Edmund G. Zelnio; Robert J. Douglass, Editor(s)

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