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Fusion of multispectral imagery and DSMs for building change detection using belief functions and reliabilities

Tian, Jiaojiao und Dezert, Jean (2019) Fusion of multispectral imagery and DSMs for building change detection using belief functions and reliabilities. International Journal of Image and Data Fusion, 10 (1), Seiten 1-27. Taylor & Francis. doi: 10.1080/19479832.2018.1513957. ISSN 1947-9832.

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Offizielle URL: https://doi.org/10.1080/19479832.2018.1513957

Kurzfassung

The extraction of building changes from very high resolution satellite images is an important but challenging task in remote sensing. Digital Surface Models (DSMs) generated from stereo imagery have proved to be valuable additional data sources for this task. In order to efficiently use the change information from the DSMs and spectral images, belief functions have .been introduced. In this article, two-step building change detection fusion models based on both Dempster-Shafer Theory (DST) and Dezert-Smarandache Theory (DSmT) frameworks are proposed. In the first step, basic belief assignments (BBAs) of the change indicators from images and DSMs are calculated by using a refined sigmoidal BBA model. Then these BBAs are employed for the new proposed building change detection decision fusion approach. In order to cover the miss-detections introduced by the wrong height values of the DSMs and incomplete information from images, disparity maps from the DSM generation procedure and shadow maps from the multispectral channels are adopted to generate reliability maps, which are further integrated to the fusion models. In the last step, building change masks are generated based on four decision-making criteria. In the experimental part of this work, we evaluate the performance of this new building change detection method on real satellite images thanks to a building change reference mask representing the ground truth. Substantial accuracy improvements are achieved when comparing the new results with those obtained from classical 3D change detection approaches.

elib-URL des Eintrags:https://elib.dlr.de/120581/
Dokumentart:Zeitschriftenbeitrag
Titel:Fusion of multispectral imagery and DSMs for building change detection using belief functions and reliabilities
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Tian, JiaojiaoJiaojiao.Tian (at) dlr.dehttps://orcid.org/0000-0002-8407-5098NICHT SPEZIFIZIERT
Dezert, Jeanjean.dezert (at) onera.frNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Januar 2019
Erschienen in:International Journal of Image and Data Fusion
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:10
DOI:10.1080/19479832.2018.1513957
Seitenbereich:Seiten 1-27
Verlag:Taylor & Francis
Name der Reihe:International Journal of Image and Data Fusion
ISSN:1947-9832
Status:veröffentlicht
Stichwörter:Change detection, belief functions, DSmT, DST, DSM
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben hochauflösende Fernerkundungsverfahren (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Methodik der Fernerkundung > Photogrammetrie und Bildanalyse
Hinterlegt von: Tian, Dr Jiaojiao
Hinterlegt am:22 Jun 2018 12:17
Letzte Änderung:20 Jun 2024 11:31

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