Dr. Ross Thornburg Profile

Dr. Ross Thornburg

at Jacobs Sverdrup Adv Sys Grp

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Proceedings Article | 2 August 2002 Paper

Evaluation methodology for hyperspectral automatic target cueing systems

Ross Thornburg, Phil Maciejewski, Rifka Claypool, Thomas Horn, Mary Jarratt, Lori Westerkamp

Proceedings Volume 4725, (2002) https://doi.org/10.1117/12.478771

KEYWORDS: Detection and tracking algorithms, Target detection, Algorithm development, Sensors, Image processing, Image analysis, Hyperspectral imaging, Automatic target recognition, Sensor performance, Spectral resolution

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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.

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