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Proceedings Paper

Frequency-band comparison using adaptive filter for multispectral imagery
Author(s): Mohammad Abu-Tahnat; Michael W. Thompson
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Paper Abstract

The detection of infrared (IR) targets immersed within an observed scene can be difficult when the target is embedded in a dominant clutter background. Multispectral IR imaging techniques for target detection have received increased attention over the past several years. This paper employs adaptive algorithms for reducing the effect of ground clutter in the presence of dependency, nonstationarity and system nonlinearities. Described are multispectral nonlinear adaptive algorithms as part of a detection scheme designed for small and/or dim point targets in IR images. Each spectral image captures a varying degree of target information. Individual scene observations and combined ones will be considered. Comparison between these frequency bands using nonlinear adaptive filters based on second order Volterra series expansion for multispectral imagery will be presented. Simulation results suggest that multispectral processing techniques have the potential for improving the detection of small and hard to find targets.

Paper Details

Date Published: 31 May 1996
PDF: 10 pages
Proc. SPIE 2765, Detection and Remediation Technologies for Mines and Minelike Targets, (31 May 1996); doi: 10.1117/12.241252
Show Author Affiliations
Mohammad Abu-Tahnat, Colorado State Univ. (United States)
Michael W. Thompson, Univ. of Texas Pan American (United States)

Published in SPIE Proceedings Vol. 2765:
Detection and Remediation Technologies for Mines and Minelike Targets
Abinash C. Dubey; Robert L. Barnard; Colin J. Lowe; John E. McFee, Editor(s)

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