Mertens, L., Sonnleitner, M., Leach, J., Agnew, M. and Padgett, M. J. (2017) Image reconstruction from photon sparse data. Scientific Reports, 7, 42164. (doi: 10.1038/srep42164) (PMID:28169363) (PMCID:PMC5294572)
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Abstract
We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Padgett, Professor Miles and Sonnleitner, Dr Matthias and Mertens, Miss Lena and Leach, Mr Jonathan |
| Authors: | Mertens, L., Sonnleitner, M., Leach, J., Agnew, M., and Padgett, M. J. |
| College/School: | College of Science and Engineering > School of Physics and Astronomy |
| Journal Name: | Scientific Reports |
| Publisher: | Nature Research |
| ISSN: | 2045-2322 |
| ISSN (Online): | 2045-2322 |
| Published Online: | 07 February 2017 |
| Copyright Holders: | Copyright © 2017 The Authors |
| First Published: | First published in Scientific Reports 7:42164 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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