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Proceedings Paper

Improved subsurface land mine recognition using high-boost fusion between passive Stokes vector imagery
Author(s): Aed El-Saba
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Paper Abstract

Detection and clearance of subsurface land mines has been one of the challenging humanitarian and military tasks. Passive polarization-based imagery has played important role achieving this task. This paper presents new fusion technique where polarization-based imagery is fused with traditional intensity imagery using high-boost approach. The main idea of the high-boost approach used in this paper is to give the polarization imagery obtained from the Stokes vector imagery more weight in forming the final fused image. It is shown that the proposed technique improves the recognition of surface land mines. This improvement is shown using correlation performance metrics derived from wavelet-filter joint-transform correlation algorithm used for pattern recognition.

Paper Details

Date Published: 26 April 2010
PDF: 9 pages
Proc. SPIE 7672, Polarization: Measurement, Analysis, and Remote Sensing IX, 76720S (26 April 2010); doi: 10.1117/12.850536
Show Author Affiliations
Aed El-Saba, Univ. of South Alabama (United States)

Published in SPIE Proceedings Vol. 7672:
Polarization: Measurement, Analysis, and Remote Sensing IX
David B. Chenault; Dennis H. Goldstein, Editor(s)

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