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Oblique aerial image matching based on iterative simulation and homography evaluation

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dc.contributor.authorSong, Woo-Hyuck-
dc.contributor.authorJung, Hong-Gyu-
dc.contributor.authorGwak, In-Youb-
dc.contributor.authorLee, Seong-Whan-
dc.date.accessioned2021-09-01T18:17:05Z-
dc.date.available2021-09-01T18:17:05Z-
dc.date.created2021-06-19-
dc.date.issued2019-03-
dc.identifier.issn0031-3203-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/67218-
dc.description.abstractThis paper presents a fast and accurate method for matching oblique aerial image pairs. In order to achieve accurate matching results, we must consider viewpoint differences between the input images in addition to rotation and scaling. Existing methods that match aerial image pairs with viewpoint differences undergo heavy computation and have difficulty finding correspondences. In this paper, we propose a homography matrix evaluation method based on a geometric approach to increase the accuracy of image matching results. In addition, we achieve faster matching through an iterative transform simulation that reduces computational complexity. Experimental results show that the proposed method improves aerial image matching in terms of computational efficiency while achieving successful matching results. (C) 2018 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.subjectFEATURES-
dc.titleOblique aerial image matching based on iterative simulation and homography evaluation-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Seong-Whan-
dc.identifier.doi10.1016/j.patcog.2018.10.027-
dc.identifier.scopusid2-s2.0-85055750336-
dc.identifier.wosid000453338200025-
dc.identifier.bibliographicCitationPATTERN RECOGNITION, v.87, pp.317 - 331-
dc.relation.isPartOfPATTERN RECOGNITION-
dc.citation.titlePATTERN RECOGNITION-
dc.citation.volume87-
dc.citation.startPage317-
dc.citation.endPage331-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusFEATURES-
dc.subject.keywordAuthorSIFT descriptor-
dc.subject.keywordAuthorFeature matching-
dc.subject.keywordAuthorAerial image-
dc.subject.keywordAuthorViewpoint change-
dc.subject.keywordAuthorNomography matrix-
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