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Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery

Qiu, Chunping and Schmitt, Michael and Zhu, Xiao Xiang (2018) Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 138, pp. 218-231. Elsevier. doi: 10.1016/j.isprsjprs.2017.12.006. ISSN 0924-2716.

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Official URL: https://www.sciencedirect.com/science/article/pii/S0924271617303830

Abstract

In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging.

Item URL in elib:https://elib.dlr.de/120084/
Document Type:Article
Title:Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Qiu, Chunpingtu münchenUNSPECIFIEDUNSPECIFIED
Schmitt, MichaelUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-LMFUNSPECIFIEDUNSPECIFIED
Date:April 2018
Journal or Publication Title:ISPRS Journal of Photogrammetry and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:138
DOI:10.1016/j.isprsjprs.2017.12.006
Page Range:pp. 218-231
Publisher:Elsevier
ISSN:0924-2716
Status:Published
Keywords:Synthetic Aperture Radar (SAR) Optical images Remote sensing Data fusion Stereogrammetry
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Hoffmann, Eike Jens
Deposited On:29 May 2018 11:27
Last Modified:02 Nov 2023 10:23

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