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12 May 2005 New methodology for predicting minimum resolvable temperature
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Abstract
The most common form of system performance check for thermal imagers is Minimum Resolvable Temperature (MRT). Viewing 4-bar patterns of various sizes, one at a time, generates an MRT plot. For each size of bar pattern, the MRT is the minimum temperature between bar and space that makes the pattern visible. Small MRT when viewing a large bar pattern indicates good system sensitivity, and small MRT when viewing a small bar pattern indicates good system resolution. Two problems make laboratory MRT difficult to predict. First, because MRT is supposed to represent the best achievable sensor performance, the operator is encouraged to change sensor gain and level for each bar pattern size. This means that the imager is not in a single gain state throughout the MRT measurement. Second, aliasing makes the MRT for sampled imagers difficult to predict. This paper describes a new model for predicting laboratory MRT. The model accounts for variation of the sensor gain during measurement. Also, the model includes the visual bandpass properties of human vision, permitting sampled imager MRT to be accurately predicted. These model changes result in MRT predictions significantly different from previous models. Model results are compared to laboratory measurements.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard Vollmerhausen and Van Hodgkin "New methodology for predicting minimum resolvable temperature", Proc. SPIE 5784, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI, (12 May 2005); https://doi.org/10.1117/12.609915
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