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Proceedings Paper

A covariance-based anomaly detector for polarimetric remote sensing applications
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Paper Abstract

The proposed paper recommends a new anomaly detection algorithm for polarimetric remote sensing applications based on the M-Box covariance test by taking advantage of key features found in a multi-polarimetric data cube. The paper demonstrates: 1) that independent polarization measurements contain information suitable for manmade object discrimination from natural clutter; 2) analysis between the variability exhibited by manmade objects relative to natural clutter; 3) comparison between the proposed M-Box covariance test with Stokes parameters S0 and S1, DoLP, RX­ Stokes, and PCA RX-Stokes; and finally 4) the data used for the comparison spans a full24-hour measurement.

Paper Details

Date Published: 21 May 2014
PDF: 13 pages
Proc. SPIE 9099, Polarization: Measurement, Analysis, and Remote Sensing XI, 90990E (21 May 2014); doi: 10.1117/12.2050398
Show Author Affiliations
Joao M. Romano, U.S. Army ARDEC (United States)
Dalton Rosario, U.S. Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 9099:
Polarization: Measurement, Analysis, and Remote Sensing XI
David B. Chenault; Dennis H. Goldstein, Editor(s)

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