Shadow Removal From Vnir Hyperspectral Remote Sensing Imagery With Endmember Signature Analysis

dc.authorid Omruuzun, Fatih/0000-0001-8164-8586
dc.authorid Daglayan, Hazan/0009-0006-4843-6913
dc.authorscopusid 55860593100
dc.authorscopusid 56780378700
dc.authorscopusid 56943462500
dc.authorscopusid 14519028500
dc.authorwosid Daglayan, Hazan/AAC-7736-2020
dc.authorwosid Omruuzun, Fatih/KMY-8310-2024
dc.contributor.author Omruuzun, Fatih
dc.contributor.author Baskurt, Didem Ozisik
dc.contributor.author Daglayan, Hazan
dc.contributor.author Cetin, Yasemin Yardimci
dc.contributor.other Computer Engineering
dc.contributor.other Software Engineering
dc.date.accessioned 2024-07-05T14:32:11Z
dc.date.available 2024-07-05T14:32:11Z
dc.date.issued 2015
dc.department Atılım University en_US
dc.department-temp [Omruuzun, Fatih; Baskurt, Didem Ozisik; Cetin, Yasemin Yardimci] Middle E Tech Univ, Dept Informat Syst, TR-06800 Ankara, Turkey; [Daglayan, Hazan] Atilim Univ, Dept Comp Engn, TR-06836 Incek, Golbasi, Turkey en_US
dc.description Omruuzun, Fatih/0000-0001-8164-8586; Daglayan, Hazan/0009-0006-4843-6913 en_US
dc.description.abstract This study aims to develop an effective regional shadow removal algorithm using rich spectral information existing in hyperspectral imagery. The proposed method benefits from spectral similarity of shadow and neighboring nonshadow pixels regardless of the intensity values. Although the shadow area has lower reflectance values due to inadequacy of incident light, it is expected that this area contains similar spectral characteristics with nonshadow area. Using this assumption, the endmembers in both shadowed and nonshadow area are extracted by Vertex Component Analysis (VCA). On the other hand, HySime algorithm overcomes estimating number of endmembers, which is one of the challenging parts in hyperspectral unmixing. Therefore, two sets of endmembers are extracted independently for both shadowed and nonshadow area. The proposed study aims at revealing the relation between these two endmember sets by comparing their pairwise similarities. Finally, reflectance values of shadowed pixels are re-calculated separately for each spectral band of hyperspectral image using this information. en_US
dc.identifier.citationcount 6
dc.identifier.doi 10.1117/12.2190066
dc.identifier.isbn 9781628415988
dc.identifier.issn 0277-786X
dc.identifier.issn 1996-756X
dc.identifier.scopus 2-s2.0-84946201990
dc.identifier.scopusquality Q4
dc.identifier.uri https://doi.org/10.1117/12.2190066
dc.identifier.uri https://hdl.handle.net/20.500.14411/757
dc.identifier.volume 9482 en_US
dc.identifier.wos WOS:000357016100039
dc.institutionauthor Başkurt, Nur Didem
dc.institutionauthor Sevim, Hazan Dağlayan
dc.language.iso en en_US
dc.publisher Spie-int Soc Optical Engineering en_US
dc.relation.ispartof Conference on Next-Generation Spectroscopic Technologies VIII -- APR 20-22, 2015 -- Baltimore, MD en_US
dc.relation.ispartofseries Proceedings of SPIE
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 9
dc.subject airborne hyperspectral imaging en_US
dc.subject shadow removal en_US
dc.subject hyperspectral unmixing en_US
dc.title Shadow Removal From Vnir Hyperspectral Remote Sensing Imagery With Endmember Signature Analysis en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 6
dspace.entity.type Publication
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