Image quality and performance modeling for automated target detection

John M. Irvine; Eric Nelson

doi:10.1117/12.818593

4 May 2009 Image quality and performance modeling for automated target detection

John M. Irvine, Eric Nelson

Proceedings Volume 7335, Automatic Target Recognition XIX; 73350L (2009) https://doi.org/10.1117/12.818593
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

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.

Citation Download Citation

John M. Irvine and Eric Nelson "Image quality and performance modeling for automated target detection", Proc. SPIE 7335, Automatic Target Recognition XIX, 73350L (4 May 2009); https://doi.org/10.1117/12.818593

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