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Proceedings Paper

Target prescreening based on 2D gamma kernels
Author(s): Jose C. Principe; Alex Radisavljevic; Munchurl Kim; John W. Fisher; Margarita Hiett; Leslie M. Novak
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Paper Abstract

This work develops and tests a new target prescreening algorithm based on 2D gamma kernels. The key feature of the new kernel set is the existence of a free parameter that determines the size of its region of support. We show that the scale affects the false alarm rate of the two parameter CFAR test. We also show that a linear discriminant funtion composed from the linear and quadratic terms of the intensity in the test cell neighborhood improves the false alarm rate when compared with the two parameter CFAR.

Paper Details

Date Published: 5 June 1995
PDF: 8 pages
Proc. SPIE 2487, Algorithms for Synthetic Aperture Radar Imagery II, (5 June 1995); doi: 10.1117/12.210842
Show Author Affiliations
Jose C. Principe, Univ. of Florida (United States)
Alex Radisavljevic, Univ. of Florida (United States)
Munchurl Kim, Univ. of Florida (United States)
John W. Fisher, Univ. of Florida (United States)
Margarita Hiett, MIT Lincoln Lab. (United States)
Leslie M. Novak, MIT Lincoln Lab. (United States)


Published in SPIE Proceedings Vol. 2487:
Algorithms for Synthetic Aperture Radar Imagery II
Dominick A. Giglio, Editor(s)

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