Imaging Components, Systems, and Processing

Radiance and photon noise: imaging in geometrical optics, physical optics, quantum optics and radiology

[+] Author Affiliations
Luca Caucci

The University of Arizona, Center for Gamma-Ray Imaging, Department of Medical Imaging, 1609 North Warren Avenue, Tucson, Arizona 85724, United States

Kyle J. Myers

U.S. Food and Drug Administration, Center for Devices and Radiological Health, Division of Imaging and Applied Mathematics, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993, United States

Harrison H. Barrett

The University of Arizona, Center for Gamma-Ray Imaging, Department of Medical Imaging, 1609 North Warren Avenue, Tucson, Arizona 85724, United States

University of Arizona, College of Optical Sciences, 1630 East University Boulevard, Tucson, Arizona 85719, United States

Opt. Eng. 55(1), 013102 (Jan 05, 2016). doi:10.1117/1.OE.55.1.013102
History: Received July 9, 2015; Accepted November 25, 2015
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Abstract.  The statistics of detector outputs produced by an imaging system are derived from basic radiometric concepts and definitions. We show that a fundamental way of describing a photon-limited imaging system is in terms of a Poisson random process in spatial, angular, and wavelength variables. We begin the paper by recalling the concept of radiance in geometrical optics, radiology, physical optics, and quantum optics. The propagation and conservation laws for radiance in each of these domains are reviewed. Building upon these concepts, we distinguish four categories of imaging detectors that all respond in some way to the incident radiance, including the new category of photon-processing detectors (capable of measuring radiance on a photon-by-photon basis). This allows us to rigorously show how the concept of radiance is related to the statistical properties of detector outputs and to the information content of a single detected photon. A Monte-Carlo technique, which is derived from the Boltzmann transport equation, is presented as a way to estimate probability density functions to be used in reconstruction from photon-processing data.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Luca Caucci ; Kyle J. Myers and Harrison H. Barrett
"Radiance and photon noise: imaging in geometrical optics, physical optics, quantum optics and radiology", Opt. Eng. 55(1), 013102 (Jan 05, 2016). ; http://dx.doi.org/10.1117/1.OE.55.1.013102


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