Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/111839
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dc.contributorDepartment of Building Environment and Energy Engineering-
dc.creatorYue, S-
dc.creatorWei, M-
dc.date.accessioned2025-03-18T01:13:05Z-
dc.date.available2025-03-18T01:13:05Z-
dc.identifier.urihttp://hdl.handle.net/10397/111839-
dc.language.isoenen_US
dc.publisherOpticaen_US
dc.rights© 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement (https://opg.optica.org/content/library/portal/item/license_v2#VOR-OA)en_US
dc.rightsJournal © 2024en_US
dc.rights© 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement (https://opg.optica.org/content/library/portal/item/license_v2#VOR-OA)en_US
dc.rights© 2024 Optica Publishing Group under the terms of the Open Access Publishing Agreement. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.en_US
dc.rightsThe following publication Shuwei Yue and Minchen Wei, "Robust pixel-wise illuminant estimation algorithm for images with a low bit-depth," Opt. Express 32, 26708-26718 (2024) is available at https://doi.org/10.1364/OE.528359.en_US
dc.titleRobust pixel-wise illuminant estimation algorithm for images with a low bit-depthen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage26708-
dc.identifier.epage26718-
dc.identifier.volume32-
dc.identifier.issue15-
dc.identifier.doi10.1364/OE.528359-
dcterms.abstractConventional illuminant estimation methods were developed for scenes with a uniform illumination, while recently developed methods, such as pixel-wise methods, estimate the illuminants at the pixel level, making them applicable to a wider range of scenes. It was found that the same pixel-wise algorithm had very different performance when applied to images with different bit-depths, with up to a 30% decrease in accuracy for images having a lower bit-depth. Image signal processing (ISP) pipelines, however, prefer to deal with images with a lower bit-depth. In this paper, the analyses show that such a reduction was due to the loss of details and increase of noises, which were never identified in the past. We propose a method combining the L1 loss optimization and physical-constrained post-processing. The proposed method was found to result in around 40% higher estimation accuracy, in comparison to the state-of-the-art DNN-based methods.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationOptics express, 2024, v. 32, no. 15, p. 26708-26718-
dcterms.isPartOfOptics express-
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85198901639-
dc.identifier.eissn1094-4087-
dc.description.validate202503 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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