Is there a best hyperspectral detection algorithm?
Name
Manolakis-2009-Is there a best hyperspectral detection algorithm.pdf
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197.98 KB
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Author(s)
Lockwood, Ronald B.
Cooley, T.
Jacobson, J.
Manolakis, Dimitris G.
Date Issued
April 2009
Journal
Proceedings of SPIE--the International Society for Optical Engineering; v.7334
Publisher
The International Society for Optical Engineering
Citation
Manolakis, D. et al. “Is there a best hyperspectral detection algorithm?.” Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV. Ed. Sylvia S. Shen & Paul E. Lewis. Orlando, FL, USA: SPIE, 2009. 733402-16. © 2009 SPIE--The International Society for Optical Engineering.
Version
Final published version
Abstract
A large number of hyperspectral detection algorithms have been developed and used over the last two decades. Some algorithms are based on highly sophisticated mathematical models and methods; others are derived using intuition and simple geometrical concepts. The purpose of this paper is threefold. First, we discuss the key issues involved in the design and evaluation of detection algorithms for hyperspectral imaging data. Second, we present a critical review of existing detection algorithms for practical hyperspectral imaging applications. Finally, we argue that the "apparent" superiority of sophisticated algorithms with simulated data or in laboratory conditions, does not necessarily translate to superiority in real-world applications.
MIT Department
Lincoln Laboratory
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
http://dx.doi.org/10.1117/12.816917
