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Proceedings Paper

Automatic ship detection from commercial multispectral satellite imagery
Author(s): Brian J. Daniel; Alan P. Schaum; Eric C. Allman; Robert A. Leathers; Trijntje V. Downes
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Paper Abstract

Commercial multispectral satellite sensors spend much of their time over the oceans. NRL has demonstrated an automatic processing system for finding ships at sea using commercially available multispectral data. To distinguish ships from whitecaps and clouds, a water/cloud clutter subspace is estimated and a continuum fusion derived anomaly detection algorithm is applied. This provides a maritime awareness capability with an acceptable detection rate while maintaining a low rate of false alarms. The system also provides a confidence metric, which can be used to further limit the false alarm rate.

Paper Details

Date Published: 18 May 2013
PDF: 8 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 874312 (18 May 2013); doi: 10.1117/12.2017762
Show Author Affiliations
Brian J. Daniel, U.S. Naval Research Lab. (United States)
Alan P. Schaum, U.S. Naval Research Lab. (United States)
Eric C. Allman, U.S. Naval Research Lab. (United States)
Robert A. Leathers, U.S. Naval Research Lab. (United States)
Trijntje V. Downes, U.S. Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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