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dc.contributor.authorWu, Di
dc.contributor.authorWetzstein, Gordon
dc.contributor.authorBarsi, Christopher
dc.contributor.authorWillwacher, Thomas
dc.contributor.authorDai, Qionghai
dc.contributor.authorRaskar, Ramesh
dc.date.accessioned2017-03-10T23:20:15Z
dc.date.available2017-03-10T23:20:15Z
dc.date.issued2013-12
dc.date.submitted2013-02
dc.identifier.issn0920-5691
dc.identifier.issn1573-1405
dc.identifier.urihttp://hdl.handle.net/1721.1/107396
dc.description.abstractLight transport has been analyzed extensively, in both the primal domain and the frequency domain. Frequency analyses often provide intuition regarding effects introduced by light propagation and interaction with optical elements; such analyses encourage optimal designs of computational cameras that efficiently capture tailored visual information. However, previous analyses have relied on instantaneous propagation of light, so that the measurement of the time dynamics of light–scene interaction, and any resulting information transfer, is precluded. In this paper, we relax the common assumption that the speed of light is infinite. We analyze free space light propagation in the frequency domain considering spatial, temporal, and angular light variation. Using this analysis, we derive analytic expressions for information transfer between these dimensions and show how this transfer can be exploited for designing a new lensless imaging system. With our frequency analysis, we also derive performance bounds for the proposed computational camera architecture and provide a mathematical framework that will also be useful for future ultra-fast computational imaging systems.en_US
dc.description.sponsorshipMIT Media Lab Consortiumen_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canadaen_US
dc.publisherSpringer USen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s11263-013-0686-0en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceSpringer USen_US
dc.titleUltra-fast Lensless Computational Imaging through 5D Frequency Analysis of Time-resolved Light Transporten_US
dc.typeArticleen_US
dc.identifier.citationWu, Di, Gordon Wetzstein, Christopher Barsi, Thomas Willwacher, Qionghai Dai, and Ramesh Raskar. “Ultra-Fast Lensless Computational Imaging through 5D Frequency Analysis of Time-Resolved Light Transport.” International Journal of Computer Vision 110, no. 2 (December 28, 2013): 128–140.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.contributor.mitauthorWu, Di
dc.contributor.mitauthorWetzstein, Gordon
dc.contributor.mitauthorBarsi, Christopher
dc.contributor.mitauthorRaskar, Ramesh
dc.relation.journalInternational Journal of Computer Visionen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2016-08-18T15:41:34Z
dc.language.rfc3066en
dc.rights.holderSpringer Science+Business Media New York
dspace.orderedauthorsWu, Di; Wetzstein, Gordon; Barsi, Christopher; Willwacher, Thomas; Dai, Qionghai; Raskar, Rameshen_US
dspace.embargo.termsNen
dc.identifier.orcidhttps://orcid.org/0000-0002-3254-3224
mit.licenseOPEN_ACCESS_POLICYen_US


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