Combining linear and nonlinear processes for multispectral material detection/identification

Tamar Peli; Mon Young; Kenneth K. Ellis

doi:10.1117/12.280604

4 August 1997 Combining linear and nonlinear processes for multispectral material detection/identification

Tamar Peli, Mon Young, Kenneth K. Ellis

Proceedings Volume 3071, Algorithms for Multispectral and Hyperspectral Imagery III; (1997) https://doi.org/10.1117/12.280604
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

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); https://doi.org/10.1117/12.280604

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