Hyperspectral target detection using sequential approach

Hanna Tran Haskett; Arun K. Sood; Mohammad K. Habib

doi:10.1117/12.359989

24 August 1999 Hyperspectral target detection using sequential approach

Hanna Tran Haskett, Arun K. Sood, Mohammad K. Habib

Proceedings Volume 3718, Automatic Target Recognition IX; (1999) https://doi.org/10.1117/12.359989
Event: AeroSense '99, 1999, Orlando, FL, United States

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.

Citation Download Citation

Hanna Tran Haskett, Arun K. Sood, and Mohammad K. Habib "Hyperspectral target detection using sequential approach", Proc. SPIE 3718, Automatic Target Recognition IX, (24 August 1999); https://doi.org/10.1117/12.359989

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