Segmentation of SAR images using improved artificial bee colony algorithm and neutrosophic set

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dc.authoridTalu, Muhammed Fatih/0000-0003-1166-8404
dc.authoridHanbay, Kazım/0000-0003-1374-1417
dc.authorwosidTalu, Muhammed Fatih/W-2834-2017
dc.authorwosidHanbay, Kazım/J-3848-2014
dc.contributor.authorHanbay, Kazim
dc.contributor.authorTalu, M. Fatih
dc.date.accessioned2024-08-04T20:39:43Z
dc.date.available2024-08-04T20:39:43Z
dc.date.issued2014
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThis paper proposes a novel synthetic aperture radar (SAR) image segmentation algorithm based on the neutrosophic set (NS) and improved artificial bee colony (I-ABC) algorithm. In this algorithm, threshold value estimation is considered as a search procedure that searches for a proper value in a grayscale interval. Therefore, I-ABC optimization algorithm is presented to search for the optimal threshold value. In order to get an efficient and powerful fitness function for I-ABC algorithm, the input SAR image is transformed into the NS domain. Then, a neutrosophic T and I subset images are obtained. A co-occurrence matrix based on the neutrosophic T and I subset images is constructed, and two-dimensional gray entropy function is described to serve as the fitness function of I-ABC algorithm. Finally, the optimal threshold value is quickly explored by the employed, onlookers and scouts bees in I-ABC algorithm. This paper contributes to SAR image segmentation in two aspects: (1) a hybrid model, having two different feature extraction methods, is proposed. (2) An optimal threshold value is automatically selected by maximizing the separability of the classes in gray level image by incorporating a simple and fast search strategy. The effectiveness of the proposed algorithm is demonstrated by application to real SAR images. (C) 2014 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.asoc.2014.04.008
dc.identifier.endpage443en_US
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.scopus2-s2.0-84901627977en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage433en_US
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2014.04.008
dc.identifier.urihttps://hdl.handle.net/11616/96466
dc.identifier.volume21en_US
dc.identifier.wosWOS:000336411500036en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofApplied Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSynthetic aperture radar (SAR) imagesen_US
dc.subjectSegmentationen_US
dc.subjectNeutrosophic seten_US
dc.subjectI-ABC algorithmen_US
dc.titleSegmentation of SAR images using improved artificial bee colony algorithm and neutrosophic seten_US
dc.typeArticleen_US

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