Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100711
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorMiao, Zen_US
dc.creatorGao, Len_US
dc.creatorHe, Yen_US
dc.creatorWu, Len_US
dc.creatorShi, Wen_US
dc.creatorSamat, Aen_US
dc.creatorLiu, Sen_US
dc.creatorLi, Jen_US
dc.date.accessioned2023-08-11T03:12:51Z-
dc.date.available2023-08-11T03:12:51Z-
dc.identifier.issn0143-1161en_US
dc.identifier.urihttp://hdl.handle.net/10397/100711-
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rights© 2018 Informa UK Limited, trading as Taylor & Francis Groupen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Remote Sensing on 02 Jan 2019 (published online), available at: http://www.tandfonline.com/10.1080/01431161.2018.1558374.en_US
dc.titleUse of colour transformation and the geodesic method for road centreline extraction from VHR satellite imagesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage4043en_US
dc.identifier.epage4058en_US
dc.identifier.volume40en_US
dc.identifier.issue10en_US
dc.identifier.doi10.1080/01431161.2018.1558374en_US
dcterms.abstractSeed point-based road extraction methods are vital for extracting road networks from satellite images. Despite its effectiveness, roads in very high-resolution (VHR) satellite images are complicated, such as road occlusion and material change. To tackle this issue, this paper proposes to use the colour space transformation and geodesic method. First, the test image is converted from Red-Green-Blue colour space to Hue-Saturation-Value colour space to reduce the material change influence. The geodesic method is subsequently applied to extract initial road segments that link road seed points provided by users. At last, the initial result is adjusted by a kernel density estimation method to produce centred roads. The presented method is quantitatively evaluated on three test images. Experiments show that the proposed method yields a substantial improvement over cutting-edge technologies. The findings in this study shine new light on a practical solution for road extraction from satellite images.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of remote sensing, 2019, v. 40, no. 10, p. 4043-4058en_US
dcterms.isPartOfInternational journal of remote sensingen_US
dcterms.issued2019-
dc.identifier.scopus2-s2.0-85059584397-
dc.identifier.eissn1366-5901en_US
dc.description.validate202305 bckw-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLSGI-0206-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Key Research and Development Program; National Natural Science Foundation of China; Natural Science Foundation of Hunan Province; Scientific Research Foundation for Distinguished Scholars, Central South University; Project of Urban Spatial Information Infrastructure for Smart City, The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS15447166-
dc.description.oaCategoryGreen (AAM)en_US
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