SAR imagery segmentation using probabilistic winner-take-all clustering

Hossam M. Osman; Steven D. Blostein

doi:10.1117/12.242050

10 June 1996 SAR imagery segmentation using probabilistic winner-take-all clustering

Hossam M. Osman, Steven D. Blostein

Proceedings Volume 2757, Algorithms for Synthetic Aperture Radar Imagery III; (1996) https://doi.org/10.1117/12.242050
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

Hossam M. Osman and Steven D. Blostein "SAR imagery segmentation using probabilistic winner-take-all clustering", Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); https://doi.org/10.1117/12.242050

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