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Proceedings Paper

Is there a best hyperspectral detection algorithm?
Author(s): D. Manolakis; R. Lockwood; T. Cooley; J. Jacobson
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Paper 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.

Paper Details

Date Published: 27 April 2009
PDF: 16 pages
Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 733402 (27 April 2009); doi: 10.1117/12.816917
Show Author Affiliations
D. Manolakis, MIT Lincoln Lab. (United States)
R. Lockwood, Air Force Research Lab. (United States)
T. Cooley, Air Force Research Lab. (United States)
J. Jacobson, National Air and Space Intelligence Ctr. (United States)

Published in SPIE Proceedings Vol. 7334:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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