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Proceedings Paper

Unconstrained eigen-filter pairs for SAR detection
Author(s): Rajesh Shenoy; David P. Casasent
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Paper Abstract

A new distortion-invariant filter algorithm for object detection in SAR imagery is presented. The filters are linear combinations of eigen-images, reject clutter, have no peak constraints, and employ false-class training. The algorithm is base on two premises: filters that separate object classes are also expected to reject clutter and using eigen-data instead of actual training images and removing fixed peak constraints improve the generalization of the filter. We describe the new filter synthesis algorithm and initial test results on six classes of SAR data.

Paper Details

Date Published: 6 March 2002
PDF: 8 pages
Proc. SPIE 4734, Optical Pattern Recognition XIII, (6 March 2002); doi: 10.1117/12.458401
Show Author Affiliations
Rajesh Shenoy, Hewlett-Packard Co. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 4734:
Optical Pattern Recognition XIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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