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Proceedings Paper

Image segmentation approach for improving target detection in a 3D signal processor
Author(s): Cheuk L. Chan; Joseph B. Attili; Kenneth A. Melendez
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Paper Abstract

The detection of small, weak targets collected from electro- optical radiation is a challenging problem, particularly in the presence of nonstationary backgrounds. In this paper, we propose a theoretical justification for the loss in performance of slowly moving targets in regions of benign clutter. In particular, a K-means segmentation technique is developed using a fixed number of classes and a variety of local scene features. This class map is used by a 3D matched filter to estimate a covariance matrix for each region. The filter would then whiten each region using the appropriate class map. The algorithm is applied in this paper to actual sensor data which contains heterogeneous scenes taken from the Airborne IR Measurement Systems sensor. Performance is assessed through the measure of SNRs and receiver operating characteristics curves based on a suite of injected targets.

Paper Details

Date Published: 3 September 1998
PDF: 8 pages
Proc. SPIE 3373, Signal and Data Processing of Small Targets 1998, (3 September 1998); doi: 10.1117/12.324609
Show Author Affiliations
Cheuk L. Chan, PAR Government Systems Corp. (United States)
Joseph B. Attili, PAR Government Systems Corp. (United States)
Kenneth A. Melendez, PAR Government Systems Corp. (United States)


Published in SPIE Proceedings Vol. 3373:
Signal and Data Processing of Small Targets 1998
Oliver E. Drummond, Editor(s)

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