Performance metrics for the evaluation of hyperspectral chemical identification systems
Author(s)
Ingle, Vinay; Truslow, Eric O.; Golowich, Steven E.; Manolakis, Dimitris G.
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Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume’s chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.
Date issued
2016-02Department
Lincoln LaboratoryJournal
Optical Engineering
Publisher
SPIE--Society of Photo-Optical Instrumentation Engineers
Citation
Truslow, Eric, Steven Golowich, Dimitris Manolakis, and Vinay Ingle. “Performance Metrics for the Evaluation of Hyperspectral Chemical Identification Systems.” Opt. Eng 55, no. 2 (February 10, 2016): 023106. ©2016 SPIE.
Version: Final published version
ISSN
0091-3286