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4 August 1997 Combining linear and nonlinear processes for multispectral material detection/identification
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tamar Peli, Mon Young, and 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);

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