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Proceedings Paper

SAR feature representation and matching using the probablistic distance transform
Author(s): David M. Doria; Eran Marcus; Alan Parks
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Paper Abstract

In this paper we present a method of fusing evidence of targets in an observed SAR image. We have selected three simple feature types to perform these initial experiments. Fusion is performed by straightforward addition of log likelihoods over feature match types. In all cases among the three feature types tested it is observed that the probability of identification improves as feature types are added. The method of recognition is based on the probabilistic distance transform (PDT). This approach derives from traditional distance transform (DT) methods of matching target predictions (based either on training or model based predictions) to observed features. The PDT method retains the basic DT matching structure, including the advantages of fast processing and non-unique correspondences between predicted and observed features, while interpreting 'distance' in terms of spatial probability densities of predicted and observed features. The PDT matching approach then results in a statistic that can be treated as a likelihood of match between an observed set of features and a predicted target signature.

Paper Details

Date Published: 24 August 2000
PDF: 10 pages
Proc. SPIE 4053, Algorithms for Synthetic Aperture Radar Imagery VII, (24 August 2000); doi: 10.1117/12.396385
Show Author Affiliations
David M. Doria, Raytheon Electronic Systems (United States)
Eran Marcus, Raytheon Electronic Systems (United States)
Alan Parks, Raytheon Electronic Systems (United States)


Published in SPIE Proceedings Vol. 4053:
Algorithms for Synthetic Aperture Radar Imagery VII
Edmund G. Zelnio, Editor(s)

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