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dc.contributor.authorHasinoff, Samuel W.
dc.contributor.authorLevin, Anat
dc.contributor.authorGoode, Philip R.
dc.contributor.authorFreeman, William T.
dc.date.accessioned2012-09-19T20:17:07Z
dc.date.available2012-09-19T20:17:07Z
dc.date.issued2011-11
dc.identifier.isbn978-1-4577-1101-5
dc.identifier.issn1550-5499
dc.identifier.urihttp://hdl.handle.net/1721.1/73057
dc.description.abstractDiffuse objects generally tell us little about the surrounding lighting, since the radiance they reflect blurs together incident lighting from many directions. In this paper we discuss how occlusion geometry can help invert diffuse reflectance to recover lighting or surface albedo. Self-occlusion in the scene can be regarded as a form of coding, creating high frequencies that improve the conditioning of diffuse light transport. Our analysis builds on a basic observation that diffuse reflectors with sufficiently detailed geometry can fully resolve the incident lighting. Using a Bayesian framework, we propose a novel reconstruction method based on high-resolution photography, taking advantage of visibility changes near occlusion boundaries. We also explore the limits of single-pixel observations as the diffuse reflector (and potentially the lighting) vary over time. Diffuse reflectance imaging is particularly relevant for astronomy applications, where diffuse reflectors arise naturally but the incident lighting and camera position cannot be controlled. To test our approaches, we first study the feasibility of using the moon as a diffuse reflector to observe the earth as seen from space. Next we present a reconstruction of Mars using historical photometry measurements not previously used for this purpose. As our results suggest, diffuse reflectance imaging expands our notion of what can qualify as a camera.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (NSERC) (Postdoctoral Fellowship)en_US
dc.description.sponsorshipUnited States-Israel Binational Science Foundation (Grant 2008155)en_US
dc.description.sponsorshipUnited States. National Geospatial-Intelligence Agency (NEGI-1582-04-0004)en_US
dc.description.sponsorshipUnited States. Multidisciplinary University Research Initiative (Grant N00014-06-1-0734)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICCV.2011.6126241en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleDiffuse reflectance imaging with astronomical applicationsen_US
dc.typeArticleen_US
dc.identifier.citationHasinoff, Samuel W. et al. “Diffuse Reflectance Imaging with Astronomical Applications.” IEEE International Conference on Computer Vision (ICCV), 2011. 185–192.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.mitauthorFreeman, William T.
dc.relation.journalIEEE International Conference on Computer Vision (ICCV), 2011en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
dspace.orderedauthorsHasinoff, Samuel W.; Levin, Anat; Goode, Philip R.; Freeman, William T.en
dc.identifier.orcidhttps://orcid.org/0000-0002-2231-7995
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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