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      Robust real-time 3D imaging of moving scenes through atmospheric obscurant using single-photon LiDAR

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          Abstract

          Recently, time-of-flight LiDAR using the single-photon detection approach has emerged as a potential solution for three-dimensional imaging in challenging measurement scenarios, such as over distances of many kilometres. The high sensitivity and picosecond timing resolution afforded by single-photon detection offers high-resolution depth profiling of remote, complex scenes while maintaining low power optical illumination. These properties are ideal for imaging in highly scattering environments such as through atmospheric obscurants, for example fog and smoke. In this paper we present the reconstruction of depth profiles of moving objects through high levels of obscurant equivalent to five attenuation lengths between transceiver and target at stand-off distances up to 150 m. We used a robust statistically based processing algorithm designed for the real time reconstruction of single-photon data obtained in the presence of atmospheric obscurant, including providing uncertainty estimates in the depth reconstruction. This demonstration of real-time 3D reconstruction of moving scenes points a way forward for high-resolution imaging from mobile platforms in degraded visual environments.

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          Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

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            The Beer-Lambert Law

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              Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging.

              The recovery of objects obscured by scattering is an important goal in imaging and has been approached by exploiting, for example, coherence properties, ballistic photons or penetrating wavelengths. Common methods use scattered light transmitted through an occluding material, although these fail if the occluder is opaque. Light is scattered not only by transmission through objects, but also by multiple reflection from diffuse surfaces in a scene. This reflected light contains information about the scene that becomes mixed by the diffuse reflections before reaching the image sensor. This mixing is difficult to decode using traditional cameras. Here we report the combination of a time-of-flight technique and computational reconstruction algorithms to untangle image information mixed by diffuse reflection. We demonstrate a three-dimensional range camera able to look around a corner using diffusely reflected light that achieves sub-millimetre depth precision and centimetre lateral precision over 40 cm×40 cm×40 cm of hidden space.
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                Author and article information

                Contributors
                r.tobin@hw.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 May 2021
                27 May 2021
                2021
                : 11
                : 11236
                Affiliations
                [1 ]GRID grid.9531.e, ISNI 0000000106567444, School of Engineering and Physical Sciences, , Heriot-Watt University, ; Edinburgh, EH14 4AS UK
                [2 ]GRID grid.417845.b, ISNI 0000 0004 0376 1104, Defence Science and Technology Laboratory, ; Porton Down, Salisbury, SP4 0LQ UK
                Article
                90587
                10.1038/s41598-021-90587-8
                8159934
                34045553
                b3b997fb-2f10-41ea-b0a1-314b27eead9a
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 January 2021
                : 11 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100010418, Defence Science and Technology Laboratory;
                Award ID: DSTLX1000108233
                Award ID: DSTLX1000095645R
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000266, Engineering and Physical Sciences Research Council;
                Award ID: EP/N003446/1
                Funded by: Royal Academy of Engineering Research Fellowship Scheme
                Award ID: RF/201718/17128
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100012339, Defence and Security Accelerator;
                Award ID: DSTLX1000147844
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                single photons and quantum effects,imaging techniques,imaging and sensing
                Uncategorized
                single photons and quantum effects, imaging techniques, imaging and sensing

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