Paper
9 May 2011 Improved noise model for the US Army sensor performance metric
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Abstract
Image noise, originating from a sensor system, is often the limiting factor in target acquisition performance. This is especially true of reflective-band sensors operating in low-light conditions. To accurately predict target acquisition range performance, image degradation introduced by the sensor must be properly combined with the limitations of the human visual system. This is modeled by adding system noise and blur to the contrast threshold function (CTF) of the human visual system, creating a combined system CTF. Current U.S. Army sensor performance models (NVThermIP, SSCAMIP, IICAM, and IINVD) do not properly address how external noise is added to the CTF as a function of display luminance. Historically, the noise calibration constant was fit from data using image intensifiers operating at low display luminance, typically much less than one foot-Lambert. However, noise calibration experiments with thermal imagery used a higher display luminance, on the order of ten foot-Lamberts, resulting in a larger noise calibration constant. To address this discrepancy, hundreds of CTF measurements were taken as a function of display luminance, apparent target angle, frame rate, noise intensity and filter shape. The experimental results show that the noise calibration constant varies as a function of display luminance. To account for this luminance dependence, a photon shot noise term representing an additional limitation in the performance of the human visual system is added to the observer model. The new noise model will be incorporated in the new U.S. Army Integrated Performance Model (NV-IPM), allowing accurate comparisons over a wide variety of sensor modalities and display luminance levels.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bradley L. Preece, Jeffrey T. Olson, Joseph P. Reynolds, and Jonathan D. Fanning "Improved noise model for the US Army sensor performance metric", Proc. SPIE 8014, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXII, 801406 (9 May 2011); https://doi.org/10.1117/12.899661
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Cited by 10 scholarly publications.
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KEYWORDS
Contrast transfer function

Calibration

Data modeling

Performance modeling

Eye models

Systems modeling

Eye

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