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Proceedings Paper

Unresolved target detection blind test project overview
Author(s): John P. Kerekes; David K. Snyder
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Paper 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.

Paper Details

Date Published: 13 May 2010
PDF: 8 pages
Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769521 (13 May 2010); doi: 10.1117/12.850321
Show Author Affiliations
John P. Kerekes, Rochester Institute of Technology (United States)
David K. Snyder, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 7695:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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