CORRECTION AND DENSIFICATION OF UAS-BASED PHOTOGRAMMETRIC THERMAL POINT CLOUD

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dc.authoridAkçay, Özgün / 0000-0003-0474-7518
dc.authoridErenoğlu, Ramazan Cüneyt / 0000-0002-8212-8379
dc.authoridErenoğlu, Oya / 0000-0003-1235-3009
dc.contributor.authorAkçay, Özgün
dc.contributor.authorErenoğlu, Ramazan Cüneyt
dc.contributor.authorErenoğlu, Oya
dc.date.accessioned2025-01-27T21:05:58Z
dc.date.available2025-01-27T21:05:58Z
dc.date.issued2016
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS) -- JUL 12-19, 2016 -- Prague, CZECH REPUBLIC
dc.description.abstractPhotogrammetric processing algorithms can suffer problems due to either the initial image quality (noise, low radiometric quality, shadows and so on) or to certain surface materials (shiny or textureless objects). This can result in noisy point clouds and/or difficulties in feature extraction. Specifically, dense point clouds which are generated with photogrammetric method using a lightweight thermal camera, are more noisy and sparse than the point clouds of high-resolution digital camera images. In this paper, new method which produces more reliable and dense thermal point cloud using the sparse thermal point cloud and high resolution digital point cloud was considered. Both thermal and digital images were obtained with UAS (Unmanned Aerial System) based lightweight Optris PI 450 and Canon EOS 605D camera images. Thermal and digital point clouds, and orthophotos were produced using photogrammetric methods. Problematic thermal point cloud was transformed to a high density thermal point cloud using image processing methods such as rasterizing, registering, interpolation and filling. The results showed that the obtained thermal point cloud - up to chosen processing parameters - was 87% more densify than the original point cloud. The second improvement was gained at the height accuracy of the thermal point cloud. New densified point cloud has more consistent elevation model while the original thermal point cloud shows serious deviations from the expected surface model.
dc.description.sponsorshipInt Soc Photogrammetry & Remote Sensing
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [114Y005]
dc.description.sponsorshipThis study was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) (Project no: 114Y005)
dc.identifier.doi10.5194/isprsarchives-XLI-B3-163-2016
dc.identifier.endpage166
dc.identifier.issn1682-1750
dc.identifier.issn2194-9034
dc.identifier.issueB3
dc.identifier.scopus2-s2.0-84978060440
dc.identifier.scopusqualityQ3
dc.identifier.startpage163
dc.identifier.urihttps://doi.org/10.5194/isprsarchives-XLI-B3-163-2016
dc.identifier.urihttps://hdl.handle.net/20.500.12428/27858
dc.identifier.volume41
dc.identifier.wosWOS:000392743800024
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherCopernicus Gesellschaft Mbh
dc.relation.ispartofXxiii Isprs Congress, Commission Iii
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20250125
dc.subjectThermal camera
dc.subjectPhotogrammetry
dc.subjectGeothermal
dc.subjectSLR Camera
dc.subjectPoint Cloud
dc.subjectUnmanned Aerial System (UAS)
dc.titleCORRECTION AND DENSIFICATION OF UAS-BASED PHOTOGRAMMETRIC THERMAL POINT CLOUD
dc.typeConference Object

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