Speirits, F. C. , Sonnleitner, M. and Barnett, S. M. (2017) From retrodiction to Bayesian quantum imaging. Journal of Optics, 19(4), 044001. (doi: 10.1088/2040-8986/aa5ccf)
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Abstract
We employ quantum retrodiction to develop a robust Bayesian algorithm for reconstructing the intensity values of an image from sparse photocount data, while also accounting for detector noise in the form of dark counts. This method yields not only a reconstructed image but also provides the full probability distribution function for the intensity at each pixel. We use simulated as well as real data to illustrate both the applications of the algorithm and the analysis options that are only available when the full probability distribution functions are known. These include calculating Bayesian credible regions for each pixel intensity, allowing an objective assessment of the reliability of the reconstructed image intensity values.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Sonnleitner, Dr Matthias and Speirits, Dr Fiona and Barnett, Professor Stephen |
| Authors: | Speirits, F. C., Sonnleitner, M., and Barnett, S. M. |
| College/School: | College of Science and Engineering > School of Physics and Astronomy |
| Journal Name: | Journal of Optics |
| Publisher: | IOP Publishing |
| ISSN: | 2040-8978 |
| ISSN (Online): | 2040-8986 |
| Published Online: | 31 January 2017 |
| Copyright Holders: | Copyright © 2017 The Authors |
| First Published: | First published in Journal of Optics 19(4):044001 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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