Paper
13 May 2010 Unresolved target detection blind test project overview
John P. Kerekes, David K. Snyder
Author Affiliations +
Abstract
The development and testing of algorithms for unresolved target detection in hyperspectral imagery requires the availability of empirical imagery with adequate ground truth. However, target deployment and collection of imagery can be expensive, and the resulting data often have limited distribution due to concerns of a security or propriety nature. When data are made available, it is usually with full ground truth leading to the possibility of analysts "tuning" their algorithm and reporting optimistic results. There exists an ongoing need for widely available, well ground truthed, and independent data for the community. This paper provides an overview and introduction to such a standard blind test data set. Airborne hyperspectral imagery is provided together with spectral reflectance signatures of several fabric panels and vehicles in the scene. A self-test image is accompanied by pixel locations in the image for the targets of interest for algorithm development. A blind test image has additional targets in different locations and is provided without pixel truth for independent performance assessment. Since publicizing the data set in 2008, over 150 researchers from around the world have downloaded the data for testing. Further details on the data, the project, and the results of participants are presented.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John P. Kerekes and David K. Snyder "Unresolved target detection blind test project overview", Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769521 (13 May 2010); https://doi.org/10.1117/12.850321
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CITATIONS
Cited by 21 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Algorithm development

Reflectivity

Target detection

Hyperspectral imaging

Hyperspectral target detection

Computer security

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