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Proceedings Paper

Broad-area search for targets in SAR imagery with context-adaptive algorithms
Author(s): Tim J. Patterson; Scott R. Fairchild
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Paper Abstract

This paper describes an ATR system based on gray scale morphology which has proven very effective in performing broad area search for targets of interest. Gray scale morphology is used to extract several distinctive sets of features which combine intensity and spatial information. Results of direct comparisons with other algorithms are presented. In a series of tests which were scored independently the morphological approach has shown superior results. An automated training systems based on a combination of genetic algorithms and classification and regression trees is described. Further performance gains are expected by allowing context sensitive selection of parameter sets for the morphological processing. Context is acquired from the image using texture measures to identify the local clutter environment. The system is designed to be able to build new classifiers on the fly to match specific image to image variations.

Paper Details

Date Published: 10 June 1996
PDF: 12 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242062
Show Author Affiliations
Tim J. Patterson, Booz-Allen & Hamilton Inc. (United States)
Scott R. Fairchild, Booz-Allen & Hamilton Inc. (United States)

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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