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dc.contributor.authorDeng, Lizhen
dc.contributor.authorZhang, Jieke
dc.contributor.authorXu, Guoxia
dc.contributor.authorZhu, Hu
dc.date.accessioned2021-03-30T08:48:57Z
dc.date.available2021-03-30T08:48:57Z
dc.date.created2021-03-23T14:00:30Z
dc.date.issued2021
dc.identifier.citationPattern Recognition. 2021, 112 107729-?.en_US
dc.identifier.issn0031-3203
dc.identifier.urihttps://hdl.handle.net/11250/2736076
dc.description.abstractTop-Hat transformation is an essential technology in the field of infrared small target detection. Many modified Top-Hat transformation methods have been proposed based on the different structure of structural elements. However, these methods are still hard to handle the dim targets and complex background. It can be summarized as two reasons, one is that the structural elements cannot suppress the background adaptively due to the fixed value of structural elements in image. Another is that simple structural element cannot utilize the local feature for target enhancement. To overcome these two limitations, a special ring Top-Hat transformation based on M-estimator and local entropy is proposed in this paper. First, an adaptive ring structural element based on M-estimator is used to suppress the complex background. Second, a novel local entropy is proposed to weight structural element for capturing local feature and target enhancement. Finally, a comparison experiment based on massive infrared image data (more than 500 infrared target images) is done. And the results demonstrate that the proposed algorithm acquires better performance compared with some recent methods.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleInfrared small target detection via adaptive M-estimator ring top-hat transformationen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber107729-?en_US
dc.source.volume112en_US
dc.source.journalPattern Recognitionen_US
dc.identifier.doi10.1016/j.patcog.2020.107729
dc.identifier.cristin1900266
dc.description.localcode"© 2020. This is the authors’ accepted and refereed manuscript to the article. Locked until 7.11.2022 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ "en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal