29 April 2016 Local retrodiction models for photon-noise-limited images
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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.
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Matthias Sonnleitner, John Jeffers, Stephen M. Barnett, "Local retrodiction models for photon-noise-limited images", Proc. SPIE 9896, Optics, Photonics and Digital Technologies for Imaging Applications IV, 98960V (29 April 2016); doi: 10.1117/12.2224444; https://doi.org/10.1117/12.2224444
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