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Proceedings Paper

Image quality and performance modeling for automated target detection
Author(s): John M. Irvine; Eric Nelson
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Paper Abstract

Several methods have been developed for quantifying the information potential of imagery exploited by a human observer. The National Imagery Interpretability Ratings Scale (NIIRS) has proven to be a useful standard for intelligence, surveillance, and reconnaissance (ISR) applications. A comparable standard for automated information extraction would be useful for a variety of applications, including tasking and collection management. This paper examines the applicability of NIIRS to automated exploitation methods. In particular, we compare image-based estimates of the NIIRS to observed performance of an automated target detection (ATD) algorithm. In addition, we examine other image metrics and their relationship to ATD performance. The findings indicate that NIIRS is not a good predictor of ATD performance, but methods that quantify the complexity of the clutter hold promise.

Paper Details

Date Published: 5 May 2009
PDF: 9 pages
Proc. SPIE 7335, Automatic Target Recognition XIX, 73350L (5 May 2009); doi: 10.1117/12.818593
Show Author Affiliations
John M. Irvine, The Charles Stark Draper Lab., Inc. (United States)
Eric Nelson, The Charles Stark Draper Lab., Inc. (United States)


Published in SPIE Proceedings Vol. 7335:
Automatic Target Recognition XIX
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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