Paper
8 January 1990 Minimum Resolvable Temperature Predictions, Test Methodology, And Data Analysis
Gerald C. Holst
Author Affiliations +
Abstract
In its current form, the NVL model does not adequately predict the laboratory measured minimum resolvable temperature (MRT) values at low or high spatial frequencies. The differences between the measured and the predicted values are caused by inappropriate modeling of the eye, tremendous variability in observers, and ill-defined data analysis methodology. In the usual laboratory procedure, the observer is allowed to move his head. This, in effect, removes the eye's response from the model because by adjusting his viewing distance, the observer appears to achieve equal detection capability at all spatial frequencies. Threshold detection can vary significantly from observer to observer and from session to session. For a large population, the detection process can be described by a log-normal distribution, and the mean MRT is the geometric average of the individual MRT responses. Geometrically averaged MRT data from three different common module-based, digital scan-converted forward-looking infrared (FLIR) systems have been compared to theoretical values. The modulation transfer function (MTF) of each FLIR was calculated using the same equations found in the NVL model. The theoretical MRT curves fit the experimental MRT data when MRT = 0.7*NEDT/MTF. For one FLIR system, the MTF was experimentally obtained by taking the Fourier transform of a slit response. The resultant MTF matched theory extremely well and therefore an objective MRT test was established.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gerald C. Holst "Minimum Resolvable Temperature Predictions, Test Methodology, And Data Analysis", Proc. SPIE 1157, Infrared Technology XV, (8 January 1990); https://doi.org/10.1117/12.978597
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KEYWORDS
Modulation transfer functions

Spatial frequencies

Forward looking infrared

Eye

Eye models

Infrared technology

Data modeling

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