4 August 1997 Combining linear and nonlinear processes for multispectral material detection/identification
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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.
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Tamar Peli, Tamar Peli, Mon Young, Mon Young, Kenneth K. Ellis, Kenneth K. Ellis, } "Combining linear and nonlinear processes for multispectral material detection/identification", Proc. SPIE 3071, Algorithms for Multispectral and Hyperspectral Imagery III, (4 August 1997); doi: 10.1117/12.280604; https://doi.org/10.1117/12.280604
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