Imaging Components, Systems, and Processing

Performance metrics for the evaluation of hyperspectral chemical identification systems

[+] Author Affiliations
Eric Truslow, Steven Golowich, Dimitris Manolakis

MIT Lincoln Laboratory, 244 Wood Street, Lexington, Massachusetts 02420-9185, United States

Vinay Ingle

Northeastern University, Department of Electrical and Computer Engineering, 360 Huntington Avenue, Boston, Massachusetts 02115, United States

Opt. Eng. 55(2), 023106 (Feb 10, 2016). doi:10.1117/1.OE.55.2.023106
History: Received June 1, 2015; Accepted January 13, 2016
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Abstract.  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.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Eric Truslow ; Steven Golowich ; Dimitris Manolakis and Vinay Ingle
"Performance metrics for the evaluation of hyperspectral chemical identification systems", Opt. Eng. 55(2), 023106 (Feb 10, 2016). ; http://dx.doi.org/10.1117/1.OE.55.2.023106


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