Altmann, Y., McLaughlin, S., Padgett, M. J. , Goyal, V. K., Hero, A. O. and Faccio, D. (2018) Quantum-inspired computational imaging. Science, 361(6403), eaat2298. (doi: 10.1126/science.aat2298) (PMID:30115781)
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Abstract
Computational imaging combines measurement and computational methods with the aim of forming images even when the measurement conditions are weak, few in number, or highly indirect. The recent surge in quantum-inspired imaging sensors, together with a new wave of algorithms allowing on-chip, scalable and robust data processing, has induced an increase of activity with notable results in the domain of low-light flux imaging and sensing. We provide an overview of the major challenges encountered in low-illumination (e.g., ultrafast) imaging and how these problems have recently been addressed for imaging applications in extreme conditions. These methods provide examples of the future imaging solutions to be developed, for which the best results are expected to arise from an efficient codesign of the sensors and data analysis tools.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Faccio, Professor Daniele and Padgett, Professor Miles |
| Authors: | Altmann, Y., McLaughlin, S., Padgett, M. J., Goyal, V. K., Hero, A. O., and Faccio, D. |
| College/School: | College of Science and Engineering > School of Physics and Astronomy |
| Journal Name: | Science |
| Publisher: | American Association for the Advancement of Science |
| ISSN: | 0036-8075 |
| ISSN (Online): | 1095-9203 |
| Copyright Holders: | Copyright © 2018 The Authors |
| First Published: | First published in Science 361(6403): eaat2298 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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