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Proceedings Paper

Local retrodiction models for photon-noise-limited images
Author(s): Matthias Sonnleitner; John Jeffers; Stephen M. Barnett
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Paper Abstract

Imaging technologies working at very low light levels acquire data by attempting to count the number of photons impinging on each pixel. Especially in cases with, on average, less than one photocount per pixel the resulting images are heavily corrupted by Poissonian noise and a host of successful algorithms trying to reconstruct the original image from this noisy data have been developed. Here we review a recently proposed scheme that complements these algorithms by calculating the full probability distribution for the local intensity distribution behind the noisy photocount measurements. Such a probabilistic treatment opens the way to hypothesis testing and confidence levels for conclusions drawn from image analysis.

Paper Details

Date Published: 29 April 2016
PDF: 12 pages
Proc. SPIE 9896, Optics, Photonics and Digital Technologies for Imaging Applications IV, 98960V (29 April 2016); doi: 10.1117/12.2224444
Show Author Affiliations
Matthias Sonnleitner, Univ. of Glasgow (United Kingdom)
John Jeffers, Univ. of Strathclyde (United Kingdom)
Stephen M. Barnett, Univ. of Glasgow (United Kingdom)


Published in SPIE Proceedings Vol. 9896:
Optics, Photonics and Digital Technologies for Imaging Applications IV
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal; Frédéric Truchetet; Pasi Saarikko, Editor(s)

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