Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/105601
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dc.contributorDepartment of Computing-
dc.creatorLiang, Zen_US
dc.creatorXu, Jen_US
dc.creatorZhang, Den_US
dc.creatorCao, Zen_US
dc.creatorZhang, Len_US
dc.date.accessioned2024-04-15T07:35:18Z-
dc.date.available2024-04-15T07:35:18Z-
dc.identifier.isbn978-1-5386-6420-9 (Electronic)en_US
dc.identifier.isbn978-1-5386-6421-6 (Print on Demand(PoD))en_US
dc.identifier.urihttp://hdl.handle.net/10397/105601-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Z. Liang, J. Xu, D. Zhang, Z. Cao and L. Zhang, "A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping," 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 2018, pp. 4758-4766 is available at https://doi.org/10.1109/CVPR.2018.00500.en_US
dc.titleA hybrid l1-l0 layer decomposition model for tone mappingen_US
dc.typeConference Paperen_US
dc.identifier.spage4758en_US
dc.identifier.epage4766en_US
dc.identifier.doi10.1109/CVPR.2018.00500en_US
dcterms.abstractTone mapping aims to reproduce a standard dynamic range image from a high dynamic range image with visual information preserved. State-of-the-art tone mapping algorithms mostly decompose an image into a base layer and a detail layer, and process them accordingly. These methods may have problems of halo artifacts and over-enhancement, due to the lack of proper priors imposed on the two layers. In this paper, we propose a hybrid ℓ 1 -ℓ 0 decomposition model to address these problems. Specifically, an ℓ 1 sparsity term is imposed on the base layer to model its piecewise smoothness property. An ℓ 0 sparsity term is imposed on the detail layer as a structural prior, which leads to piecewise constant effect. We further propose a multiscale tone mapping scheme based on our layer decomposition model. Experiments show that our tone mapping algorithm achieves visually compelling results with little halo artifacts, outperforming the state-of-the-art tone mapping algorithms in both subjective and objective evaluations.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 18 - 22 June 2018, Salt Lake City, Utah, p. 4758-4766en_US
dcterms.issued2018-
dc.identifier.scopus2-s2.0-85059631249-
dc.relation.conferenceConference on Computer Vision and Pattern Recognition [CVPR]-
dc.description.validate202402 bcch-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCOMP-0761-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNSFCen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS14959073-
dc.description.oaCategoryGreen (AAM)en_US
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