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Fusion of TanDEM-X and Cartosat-1 DEMs using TV-Norm Regularization and ANN-Predicted Weights

Bagheri, Hossein and Schmitt, Michael and Zhu, Xiao Xiang (2017) Fusion of TanDEM-X and Cartosat-1 DEMs using TV-Norm Regularization and ANN-Predicted Weights. In: Proceedings of IEEE Geoscience and Remote Sensing Symposium, pp. 3369-3372. IGARSS 2017, 23.-28. Juli 2017, Fort Worth, USA.

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Abstract

This paper deals with TanDEM-X and Cartosat-1 DEM fusion over urban areas with support of weight maps predicted by an artificial neural network (ANN). Although the TanDEM-X DEM is a global elevation dataset of unprecedented accuracy (following HRTI-3 standard), its quality decreases over urban areas because of artifacts intrinsic to the SAR imaging geometry. DEM fusion techniques can be used to improve the TanDEM-X DEM in problematic areas. In this investigation, Cartosat-1 elevation data were fused with the TanDEMX DEM by weighted averaging and total variation (TV)-based regularization, resorting to weight maps derived by a specifically trained ANN. The results show that the proposed fusion strategy can significantly improve the final DEM quality.

Item URL in elib:https://elib.dlr.de/116073/
Document Type:Conference or Workshop Item (Poster)
Title:Fusion of TanDEM-X and Cartosat-1 DEMs using TV-Norm Regularization and ANN-Predicted Weights
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bagheri, Hosseintu münchenUNSPECIFIED
Schmitt, Michaelm.schmitt (at) tum.deUNSPECIFIED
Zhu, Xiao Xiangdlr-imf/tum-lmfUNSPECIFIED
Date:2017
Journal or Publication Title:Proceedings of IEEE Geoscience and Remote Sensing Symposium
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 3369-3372
Status:Published
Keywords:Fusion, TanDEM-X, Cartosat-1, TV-Norm
Event Title:IGARSS 2017
Event Location:Fort Worth, USA
Event Type:international Conference
Event Dates:23.-28. Juli 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Häberle, Matthias
Deposited On:06 Dec 2017 12:59
Last Modified:31 Jul 2019 20:13

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