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dc.contributor.authorBiswas, Biswajit
dc.contributor.authorBhattacharyya, Siddhartha
dc.contributor.authorPlatoš, Jan
dc.contributor.authorSnášel, Václav
dc.date.accessioned2019-10-21T08:53:49Z
dc.date.available2019-10-21T08:53:49Z
dc.date.issued2019
dc.identifier.citationInformation Sciences. 2019, vol. 500, p. 67-86.cs
dc.identifier.issn0020-0255
dc.identifier.issn1872-6291
dc.identifier.urihttp://hdl.handle.net/10084/138874
dc.description.abstractIn this paper, we address the hesitant information in enhancement task often caused by differences in image contrast. Enhancement approaches generally use certain filters which generate artifacts or are unable to recover all the objects details in images. Typically, the contrast of an image quantifies a unique ratio between the amounts of black and white through a single pixel. However, contrast is better represented by a group of pix- els. We have proposed a novel image enhancement scheme based on intuitionistic hesi- tant fuzzy sets (IHFSs) for drone images (dronogram) to facilitate better interpretations of target objects. First, a given dronogram is divided into foreground and background areas based on an estimated threshold from which the proposed model measures the amount of black/white intensity levels. Next, we fuzzify both of them and determine the hesitant score indicated by the distance between the two areas for each point in the fuzzy plane. Finally, a hyperbolic operator is adopted for each membership grade to improve the pho- tographic quality leading to enhanced results via defuzzification. The proposed method is tested on a large drone image database. Results demonstrate better contrast enhancement, improved visual quality, and better recognition compared to the state-of-the-art methods.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesInformation Sciencescs
dc.relation.urihttp://doi.org/10.1016/j.ins.2019.05.069cs
dc.rights© 2019 The Authors. Published by Elsevier Inc.cs
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/cs
dc.subjectvisual enhancementcs
dc.subjectdrone imagecs
dc.subjectfuzzy setcs
dc.subjectintuitionistic fuzzy setcs
dc.subjecthesitant setcs
dc.subjecthesitant scorecs
dc.titleEnhancement of dronogram aid to visual interpretation of target objects via intuitionistic fuzzy hesitant setscs
dc.typearticlecs
dc.identifier.doi10.1016/j.ins.2019.05.069
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume500cs
dc.description.lastpage86cs
dc.description.firstpage67cs
dc.identifier.wos000478711700005


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© 2019 The Authors. Published by Elsevier Inc.
Except where otherwise noted, this item's license is described as © 2019 The Authors. Published by Elsevier Inc.