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Autoren:
Recla, Michael; Schmitt, Michael 
Dokumenttyp:
Zeitschriftenartikel / Journal Article 
Titel:
The SAR2Height framework for urban height map reconstruction from single SAR intensity images 
Zeitschrift:
ISPRS Journal of Photogrammetry and Remote Sensing 
Jahrgang:
211 
Jahr:
2024 
Seiten von - bis:
104-120 
Sprache:
Englisch 
Stichwörter:
Single image height estimation ; Synthetic Aperture Radar (SAR) ; 3D reconstruction ; Radargrammetry ; Urban areas ; Deep learning 
Abstract:
Recently, it was shown that a detailed reconstruction of urban height maps is possible from single very high resolution (VHR) synthetic aperture radar (SAR) images with deep convolutional neural networks. Being merely a proof-of-concept so far, the potential of this approach has not been fully exploited yet. With this work, we present an optimized deep learning model for height estimation from single VHR SAR images, which incorporates sensor knowledge into the estimation. We embed this model int...    »
 
ISSN:
0924-2716 
Fakultät:
Fakultät für Luft- und Raumfahrttechnik 
Institut:
LRT 9 - Institut für Raumfahrttechnik und Weltraumnutzung 
Professur:
Schmitt, Michael 
Open Access ja oder nein?:
Ja / Yes 
Art der OA-Lizenz:
CC BY 4.0