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dc.contributor.authorShin, Dongeeken_US
dc.contributor.authorXu, Feihuen_US
dc.contributor.authorWong, Franco N.C.en_US
dc.contributor.authorShapiro, Jeffrey H.en_US
dc.contributor.authorGoyal, Vivek K.en_US
dc.date.accessioned2020-01-28T17:11:32Z
dc.date.available2020-01-28T17:11:32Z
dc.date.issued2016-02-08
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000371427100003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationDongeek Shin, Feihu Xu, Franco NC Wong, Jeffrey H Shapiro, Vivek K Goyal. 2016. "Computational multi-depth single-photon imaging." OPTICS EXPRESS, Volume 24, Issue 3, pp. 1873 - 1888. https://doi.org/10.1364/OE.24.001873
dc.identifier.issn1094-4087
dc.identifier.urihttps://hdl.handle.net/2144/39191
dc.description.abstractWe present an imaging framework that is able to accurately reconstruct multiple depths at individual pixels from single-photon observations. Our active imaging method models the single-photon detection statistics from multiple reflectors within a pixel, and it also exploits the fact that a multi-depth profile at each pixel can be expressed as a sparse signal. We interpret the multi-depth reconstruction problem as a sparse deconvolution problem using single-photon observations, create a convex problem through discretization and relaxation, and use a modified iterative shrinkage-thresholding algorithm to efficiently solve for the optimal multi-depth solution. We experimentally demonstrate that the proposed framework is able to accurately reconstruct the depth features of an object that is behind a partially-reflecting scatterer and 4 m away from the imager with root mean-square error of 11 cm, using only 19 signal photon detections per pixel in the presence of moderate background light. In terms of root mean-square error, this is a factor of 4.2 improvement over the conventional method of Gaussian-mixture fitting for multi-depth recovery.en_US
dc.description.sponsorshipThis material is based upon work supported in part by a Samsung Scholarship, the US National Science Foundation under Grant No. 1422034, and the MIT Lincoln Laboratory Advanced Concepts Committee. We thank Dheera Venkatraman for his assistance with the experiments. (Samsung Scholarship; 1422034 - US National Science Foundation; MIT Lincoln Laboratory Advanced Concepts Committee)en_US
dc.format.extentpp. 1873 - 1888en_US
dc.languageEnglish
dc.publisherOPTICAL SOC AMERen_US
dc.relation.ispartofOPTICS EXPRESS
dc.rightsCopyright 2016 Optical Society of America. The final author draft of this article is being made available in OpenBU under Boston University's open access.policy.en_US
dc.subjectThree-dimensional image acquisitionen_US
dc.subjectOpticsen_US
dc.subjectLidaren_US
dc.subjectCMOSen_US
dc.subject3Den_US
dc.subjectOptical physicsen_US
dc.subjectCommunications technologiesen_US
dc.subjectElectrical and electronic engineeringen_US
dc.titleComputational multi-depth single-photon imagingen_US
dc.typeArticleen_US
dc.description.versionAccepted manuscripten_US
dc.identifier.doi10.1364/OE.24.001873
pubs.elements-sourceweb-of-scienceen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Electrical & Computer Engineeringen_US
pubs.publication-statusPublisheden_US
dc.identifier.mycv117495


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