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Proceedings Paper

Combining linear and nonlinear processes for multispectral material detection/identification
Author(s): Tamar Peli; Mon Young; Kenneth K. Ellis
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Paper Abstract

This paper describes a novel multi-spectral algorithm that combines linear and nonlinear processes to detect and identify materials with known spectral signatures. The nonlinear multi-spectral process is an anomaly detector that applies geometric whitening filters. It has demonstrated good detection and false alarm rejection performances without the knowledge of a prior target spectral information. In some instances, it achieved performance equivalent to material identification just by proper selection of spectral bands. This capability, i.e. material identification, was greatly enhanced by the incorporation of a priori target statistics.

Paper Details

Date Published: 4 August 1997
PDF: 12 pages
Proc. SPIE 3071, Algorithms for Multispectral and Hyperspectral Imagery III, (4 August 1997); doi: 10.1117/12.280604
Show Author Affiliations
Tamar Peli, Atlantic Aerospace Electronics Corp. (United States)
Mon Young, Atlantic Aerospace Electronics Corp. (United States)
Kenneth K. Ellis, Atlantic Aerospace Electronics (United States)


Published in SPIE Proceedings Vol. 3071:
Algorithms for Multispectral and Hyperspectral Imagery III
A. Evan Iverson; Sylvia S. Shen, Editor(s)

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