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Proceedings Paper

Evaluation of automated algorithms for small target detection and non-natural terrain characterization using remote multi-band imagery
Author(s): Eric Hallenborg; David L. Buck; Erin Daly
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Paper Abstract

Experimental remote sensing data from the 8 to 12 μm wavelength NASA Thermal Infrared Multispectral Scanner (TIMS) have been a valuable resource for multispectral algorithm proof-of-concept, a prime example being a Constant False Alarm Rate (CFAR) spectral small target detector founded on maximum likelihood theory; CFAR tests on low signal-to-clutter ratio rural Australian TIMS imagery yielded a detection rate of 5 out of 7 (71%) for small extended targets, e.g. buildings ~ 10 meters in extent, at a 10-6 false alarm rate. Separately, techniques such as Independent Component Analysis (ICA) have since shown good promise for small target detection as well as terrain feature extraction. In this study, we first provide higher-confidence CFAR performance estimates by incorporating a larger set of imagery including ASTER satellite multi-band imagery and ground truth. Secondly, alongside CFAR we perform ICA, which effectively separates many non-natural features from the highly cluttered natural terrain background; in particular, our TIMS results show that a surprisingly small subset of ICA components contain the majority of nonnatural "signal" such as paved roads amid the clutter of soil, rock, and vegetation.

Paper Details

Date Published: 17 September 2011
PDF: 10 pages
Proc. SPIE 8137, Signal and Data Processing of Small Targets 2011, 813711 (17 September 2011); doi: 10.1117/12.895764
Show Author Affiliations
Eric Hallenborg, Space and Naval Warfare Systems Ctr. Pacific (United States)
David L. Buck, Space and Naval Warfare Systems Ctr. Pacific (United States)
Erin Daly, Space and Naval Warfare Systems Ctr. Pacific (United States)


Published in SPIE Proceedings Vol. 8137:
Signal and Data Processing of Small Targets 2011
Oliver E. Drummond, Editor(s)

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