
Proceedings Paper
A wavelet contrast metric for the targeting task performance metricFormat | Member Price | Non-Member Price |
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Paper Abstract
Target acquisition performance depends strongly on the contrast of the target. The Targeting Task Performance (TTP)
metric, within the Night Vision Integrated Performance Model (NV-IPM), uses a combination of resolution, signal-to-noise
ratio (SNR), and contrast to predict and model system performance. While the dependence on resolution and SNR
are well defined and understood, defining a robust and versatile contrast metric for a wide variety of acquisition tasks is
more difficult. In this correspondence, a wavelet contrast metric (WCM) is developed under the assumption that the
human eye processes spatial differences in a manner similar to a wavelet transform. The amount of perceivable
information, or useful wavelet coefficients, is used to predict the total viewable contrast to the human eye. The WCM is
intended to better match the measured performance of the human vision system for high-contrast, low-contrast, and low-observable
targets. After further validation, the new contrast metric can be incorporated using a modified TTP metric
into the latest Army target acquisition software suite, the NV-IPM.
Paper Details
Date Published: 24 June 2016
PDF: 11 pages
Proc. SPIE 9820, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVII, 98200E (24 June 2016); doi: 10.1117/12.2223855
Published in SPIE Proceedings Vol. 9820:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVII
Gerald C. Holst; Keith A. Krapels, Editor(s)
PDF: 11 pages
Proc. SPIE 9820, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVII, 98200E (24 June 2016); doi: 10.1117/12.2223855
Show Author Affiliations
Bradley L. Preece, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Eric A. Flug, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Published in SPIE Proceedings Vol. 9820:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXVII
Gerald C. Holst; Keith A. Krapels, Editor(s)
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