The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis -the prediction of image quality from fundamental design parameters -is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.
The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. The National Imagery Interpretability Rating Scale (NIIRS) is a useful measure of image quality, because, by characterizing the overall interpretability of an image, it combines into one metric those contributors to image quality to which a human interpreter is most sensitive. The main drawback to using a NIIRS rating as a measure of image quality in engineering trade studies is the fact that it is tied to the human observer and cannot be predicted from physical principles and engineering parameters alone. The General Image Quality Equation (GIQE) of Leachtenauer et al. 1997 [Appl. Opt. 36, 8322-8328 (1997] is a regression of actual image analyst NIIRS ratings vs. readily calculable engineering metrics, and provides a mechanism for using the expected NIIRS rating of an imaging system in the design and evaluation process. In this paper, we will discuss how we use the GIQE in conjunction with The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) to evaluate imager designs, taking a hypothetical high resolution commercial imaging system as an example.
In a previous paper in this series, we described how The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) tool may be used to model space and airborne imaging systems operating in the visible to near-infrared (VISNIR). PICASSO is a systems-level tool, representative of a class of such tools used throughout the remote sensing community. It is capable of modeling systems over a wide range of fidelity, anywhere from conceptual design level (where it can serve as an integral part of the systems engineering process) to as-built hardware (where it can serve as part of the verification process). In the present paper, we extend the discussion of PICASSO to the modeling of Thermal Infrared (TIR) remote sensing systems, presenting the equations and methods necessary to modeling in that regime.
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