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dc.contributor.authorZhu, Hu
dc.contributor.authorXu, Guoxia
dc.contributor.authorLiu, Lu
dc.contributor.authorDeng, Lizhen
dc.date.accessioned2021-04-21T08:16:15Z
dc.date.available2021-04-21T08:16:15Z
dc.date.created2021-03-23T15:35:56Z
dc.date.issued2021
dc.identifier.citationConcurrency and Computation. 2021, .en_US
dc.identifier.issn1532-0626
dc.identifier.urihttps://hdl.handle.net/11250/2738773
dc.description.abstractSmoke has a very bad effect on the outdoor vision system. Not only are the videos with poor visual effects obtained, but also the quality and structure of the videos are reduced. In this paper, we propose a video smoke removal method based on low‐rank tensor completion via spatial‐temporal continuity constraint. The proposed method is based on the smoke mixing model and consider the sparseness of smoke and the global and local consistency of clean video. Then, the optimal solution of the smoke removal algorithm model is quickly realized by the Alternating Direction Method of Multiplier. Finally, we evaluate the experiment results of real‐world data and simulated data from the visual effects and objective indicators. And the experiment results show that our proposed algorithm can achieve better smoke removal results.en_US
dc.language.isoengen_US
dc.publisherJohn Wiley & Sons, Ltd.en_US
dc.titleVideo smoke removal based on low‐rank tensor completion via spatial‐temporal continuity constrainten_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.source.journalConcurrency and Computationen_US
dc.identifier.doi10.1002/cpe.6169
dc.identifier.cristin1900318
dc.description.localcodeLocked until 26 January 2022 due to copyright restrictions. This is the peer reviewed version of an article, which has been published in final form at https://doi.org/10.1002/cpe.6169. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.en_US
dc.source.articlenumbere6169en_US
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode2


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