Imager performance assessment with TRM4 version 3: an overview

Electro-Optical and Infrared Systems: Technology and Applications XVIII and Electro-Optical Remote Sensing XV(2021)

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摘要
Model-based performance assessment is a valuable approach in the process of designing or comparing electrooptical and infrared imagers since it alleviates the need for expensive field measurement campaigns. TRM4 serves this purpose and is primarily used to calculate the range performance based on parameters of the imaging system and the environmental conditions. It features a validated approach to consider aliasing in the performance assessment of sampled imagers. This paper highlights new features and major changes in TRM4.v3, which is to be released in autumn 2021. TRM4.v3 includes the calculation of an image quality metric based on the National Imagery Interpretability Rating Scale (NIIRS). The NIIRS value computation is based on the latest version of the General Image Quality Equation. This extends the performance assessment capability of TRM4 in particular to imagers used for aerial imaging. The three-dimensional target modelling was revised to cope with a wider range of scenarios: from ground imaging of aerial targets against a sky background to aerial imaging of ground targets, including groundto-ground imaging. For imagers working in the visible to the SWIR spectral range, TRM4.v3 provides not only an improved comparison basis between lab measurements and modelling, but also allows direct integration of measured device data. This is achieved by introducing and computing (in analogy to the Minimum Temperature Difference Perceived used for thermal imagers) the so-called Minimum Contrast Perceived (MCP). This device figure of merit is similar to the Minimum Resolvable Contrast (MRC) but also applicable at frequencies above Nyquist frequency. Using measured MCP or MRC data, range performance can be calculated for devices such as cameras, telescopic sights and night vision goggles. In addition, the intensified camera module introduced in a previous publication was further elaborated and a comparison to laboratory measurement results is presented. Lastly, the graphical user interface was improved to provide a better user experience. Specifically, an interactive user assistance in form of tooltips was introduced.
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imager performance assessment,trm4 version
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