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Computational and dark-field ghost imaging with ultraviolet light

dc.contributor.authorSong, Jiaqi
dc.contributor.authorLiu, Baolei
dc.contributor.authorWANG, YAO
dc.contributor.authorChen, Chaohao
dc.contributor.authorShan, Xuchen
dc.contributor.authorZHONG, XIAOLAN
dc.contributor.authorWU, LING-AN
dc.contributor.authorWANG, FAN
dc.date.accessioned2024-08-12T05:50:57Z
dc.date.available2024-08-12T05:50:57Z
dc.date.issued2024
dc.date.updated2024-05-12T08:15:59Z
dc.description.abstractUltraviolet (UV) imaging enables a diverse array of applications, such as material composition analysis, biological fluorescence imaging, and detecting defects in semiconductor manufacturing. However, scientific-grade UV cameras with high quantum efficiency are expensive and include complex thermoelectric cooling systems. Here, we demonstrate a UV computational ghost imaging (UV-CGI) method to provide a cost-effective UV imaging and detection strategy. By applying spatial–temporal illumination patterns and using a 325 nm laser source, a single-pixel detector is enough to reconstruct the images of objects. We use UV-CGI to distinguish four UV-sensitive sunscreen areas with different densities on a sample. Furthermore, we demonstrate dark-field UV-CGI in both transmission and reflection schemes. By only collecting the scattered light from objects, we can detect the edges of pure phase objects and small scratches on a compact disc. Our results showcase a feasible low-cost solution for nondestructive UV imaging and detection. By combining it with other imaging techniques, such as hyperspectral imaging or time-resolved imaging, a compact and versatile UV computational imaging platform may be realized for future applications.
dc.description.sponsorshipNational Natural Science Foundation of China (62075004, 62275010, 11804018); China Postdoctoral Science Foundation (2022M720347, 2022TQ0020); Beijing Municipal Natural Science Foundation (4212051, 1232027); International Postdoctoral Exchange Fellowship Program (YJ20220241, YJ20220037); Fundamental Research Funds for the Central Universities.
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2327-9125
dc.identifier.urihttps://hdl.handle.net/1885/733714613
dc.language.isoen_AUen_AU
dc.provenancePublished by Optica Publishing Group under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
dc.publisherOptical Society of America
dc.rights© 2024 The authors
dc.rights.licenseCreative Commons Attribution licence
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePhotonics Research
dc.titleComputational and dark-field ghost imaging with ultraviolet light
dc.typeJournal article
dcterms.accessRightsOpen Access
local.bibliographicCitation.issue2
local.bibliographicCitation.lastpage234
local.bibliographicCitation.startpage226
local.contributor.affiliationSong, Jiaqi, School of Physics, Beihang University
local.contributor.affiliationLiu, Baolei, Beihang University
local.contributor.affiliationWANG, YAO, School of Physics, Beihang University
local.contributor.affiliationChen, Chaohao, College of Science, ANU
local.contributor.affiliationShan, Xuchen, Beihang University
local.contributor.affiliationZHONG, XIAOLAN, School of Physics, Beihang University
local.contributor.affiliationWU, LING-AN, Institute of Physics, Chinese Academy of Sciences
local.contributor.affiliationWANG, FAN, School of Physics, Beihang University
local.contributor.authoruidChen, Chaohao, u1143421
local.description.notesImported from ARIES
local.identifier.absfor510204 - Photonics, optoelectronics and optical communications
local.identifier.ariespublicationa383154xPUB46917
local.identifier.citationvolume12
local.identifier.doi10.1364/PRJ.503974
local.identifier.scopusID2-s2.0-85184840107
local.publisher.urlhttps://opg.optica.org/
local.type.statusPublished Version
publicationvolume.volumeNumber12

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