1 June 2005 Taxonomy of detection algorithms for hyperspectral imaging applications
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Optical Engineering, 44(6), 066403 (2005). doi:10.1117/1.1930927
Abstract
A unified, simplified, and concise overview of spectral target detection algorithms for hyperspectral imaging applications is presented. We focus on detection algorithms derived using established statistical techniques and whose performance is predictable under reasonable assumptions about hyperspectral imaging data. The emphasis on a signal processing perspective enables us to better understand the strengths and limitations of each algorithm, avoid unrealistic performance expectations, and apply an algorithm properly and sensibly.
Dimitris G. Manolakis, "Taxonomy of detection algorithms for hyperspectral imaging applications," Optical Engineering 44(6), 066403 (1 June 2005). http://dx.doi.org/10.1117/1.1930927
JOURNAL ARTICLE
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KEYWORDS
Detection and tracking algorithms

Sensors

Target detection

Taxonomy

Data modeling

Hyperspectral imaging

Algorithm development

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