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dc.contributor.authorYin, Jianfeng
dc.contributor.authorCooperstock, Jeremy R.
dc.contributor.editorSkala, Václav
dc.date.accessioned2013-04-22T12:44:14Z
dc.date.available2013-04-22T12:44:14Z
dc.date.issued2004
dc.identifier.citationJournal of WSCG. 2004, vol. 12, no. 1-3, p. 499-506.en
dc.identifier.issn1213-6972
dc.identifier.urihttp://wscg.zcu.cz/wscg2004/Papers_2004_Full/N97.pdf
dc.identifier.urihttp://hdl.handle.net/11025/1746
dc.description.abstractDue to differing optics, sensor characteristics, and hardware processing employed by video cameras, the resulting colors produced by two cameras can be very different, thus complicating the task of computer vision applications. While various color correction methods exist to deal with this problem, most involve strong assumptions, such as constant illumination, that are, in general, unsatisfied in complex environments. To address the problem of color correction in a less restrictive manner, we propose the use of neural networks, which can easily be trained and which produce excellent results. We compare these results with other methods.en
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherUNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© UNION Agencycs
dc.subjectbarevná korekcecs
dc.subjectdigitální projekcecs
dc.titleColor correction methods with applications to digital projection environmentsen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedcolor correctionen
dc.subject.translateddigital projectionen
dc.type.statusPeer-revieweden
Appears in Collections:Volume 12, number 1-3 (2004)

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