The use of the general image quality equation in the design and evaluation of imaging systems

Steve A. Cota; Christopher J. Florio; David J. Duvall; Michael A. Leon

doi:10.1117/12.829024

12 August 2009 The use of the general image quality equation in the design and evaluation of imaging systems

Steve A. Cota, Christopher J. Florio, David J. Duvall, Michael A. Leon

Proceedings Volume 7458, Remote Sensing System Engineering II; 74580H (2009) https://doi.org/10.1117/12.829024
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

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.

Citation Download Citation

Steve A. Cota, Christopher J. Florio, David J. Duvall, and Michael A. Leon "The use of the general image quality equation in the design and evaluation of imaging systems", Proc. SPIE 7458, Remote Sensing System Engineering II, 74580H (12 August 2009); https://doi.org/10.1117/12.829024

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