Broad-area search for targets in SAR imagery with context-adaptive algorithms

Tim J. Patterson; Scott R. Fairchild

doi:10.1117/12.242062

10 June 1996 Broad-area search for targets in SAR imagery with context-adaptive algorithms

Tim J. Patterson, Scott R. Fairchild

Proceedings Volume 2757, Algorithms for Synthetic Aperture Radar Imagery III; (1996) https://doi.org/10.1117/12.242062
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

Tim J. Patterson and Scott R. Fairchild "Broad-area search for targets in SAR imagery with context-adaptive algorithms", Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); https://doi.org/10.1117/12.242062

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KEYWORDS

Synthetic aperture radar

Detection and tracking algorithms

Feature extraction

Automatic target recognition

Genetic algorithms

Target detection

Genetics

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