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Proceedings Paper

Evaluation methodology for hyperspectral automatic target cueing systems
Author(s): Ross Thornburg; Phil Maciejewski; Rifka Claypool; Thomas J. Horn; Mary Jarratt; Lori A. Westerkamp
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Paper Abstract

Because of its fine wavelength resolution, hyperspectral imaging (HSI) offers the possibility of detecting and identifying objects of interest by their spectral characteristics. The Automatic Target Cueing, Detection and Recognition (ATC/D/R) community is developing new methods to predict and measure HSI ATC/D/R systems performance. The variation of spectral signatures due to target characteristics, atmospheric effects, and other environmental factors contribute to the challenge of developing and evaluating robust algorithms for HSI ATC/D/R systems. A rigorous method for test and evaluation is necessary to determine system performance and define the most efficient and effective sensor/algorithm solutions for a proposed mission. The AFRL Sensors Directorate Comprehensive Performance Assessment of Sensor Exploitation (COMPASE) Center has developed standardized tools and methods that permit performance comparison of candidate ATC algorithms1,2. This paper defines the methodology employed for an independent evaluation of HSI ATC algorithms. The performance metrics, truthing and scoring techniques, and the importance of understanding the operating conditions (OCs) represented by each data set are discussed. The OC definitions for spectral systems are different from the OCs as defined by radar systems. The environmental considerations drive data collection planning and truthing requirements. Knowledge of performance of an algorithm in different OCs is essential information when considering the transition of an HSI sensor/algorithm system or the design of future HS algorithms.

Paper Details

Date Published: 2 August 2002
PDF: 10 pages
Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); doi: 10.1117/12.478771
Show Author Affiliations
Ross Thornburg, Jacobs Sverdrup Technology Inc. (United States)
Phil Maciejewski, Jacobs Sverdurp Technology Inc. (United States)
Rifka Claypool, Jacobs Sverdurp Technology Inc. (United States)
Thomas J. Horn, Jacobs Sverdrup Technology, Inc. (United States)
Mary Jarratt, Air Force Research Lab. (United States)
Lori A. Westerkamp, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 4725:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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