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Optical Engineering

Taxonomy of detection algorithms for hyperspectral imaging applications
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Paper 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.

Paper Details

Date Published: 1 June 2005
PDF: 11 pages
Opt. Eng. 44(6) 066403 doi: 10.1117/1.1930927
Published in: Optical Engineering Volume 44, Issue 6
Show Author Affiliations
Dimitris G. Manolakis, MIT Lincoln Lab. (United States)

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