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Proceedings Paper

Hyperspectral target detection using sequential approach
Author(s): Hanna Tran Haskett; Arun K. Sood; Mohammad K. Habib
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Paper Abstract

This paper describes an automatic target detection algorithm based on the sequential multi-stage approach. Each stage of the algorithm uses more spectral bands than the previous stage. To ensure high probability of detection and low false alarm rate, Chebyshev's inequality test is applied. The sequential approach enables a significant reduction in computational time of a hyperspectral detection system. The Forest Radiance I database collected with the HYDICE hyperspectral sensor at the U.S. Army Proving Ground in Aberdeen, Maryland is utilized. Scenarios include targets in the open, with footprints of 1 m and different times of day. The total area coverage and the number of targets used in this evaluation are approximately 6 km2 and 126, respectively.

Paper Details

Date Published: 24 August 1999
PDF: 10 pages
Proc. SPIE 3718, Automatic Target Recognition IX, (24 August 1999); doi: 10.1117/12.359989
Show Author Affiliations
Hanna Tran Haskett, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Arun K. Sood, George Mason Univ. (United States)
Mohammad K. Habib, George Mason Univ. (United States)


Published in SPIE Proceedings Vol. 3718:
Automatic Target Recognition IX
Firooz A. Sadjadi, Editor(s)

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