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Proceedings Paper

SPICE: a sparsity promoting iterated constrained endmember extraction algorithm with applications to landmine detection from hyperspectral imagery
Author(s): Alina Zare; Paul Gader
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Paper Abstract

An extension of the Iterated Constrained Endmembers (ICE) algorithm that incorporates sparsity promoting priors to find the correct number of endmembers is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine the number of endmembers required for a particular scene. The number of endmembers is found by adding a sparsity-promoting term to ICE's objective function. This method is applied to long wave infrared, LWIR, hyperspectral data to seek out vegetation endmembers and define a vegetation mask for the reduction of false alarms in landmine data.

Paper Details

Date Published: 26 April 2007
PDF: 9 pages
Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 655319 (26 April 2007); doi: 10.1117/12.722595
Show Author Affiliations
Alina Zare, Univ. of Florida (United States)
Paul Gader, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 6553:
Detection and Remediation Technologies for Mines and Minelike Targets XII
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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