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Automatic registration of SAR image and GIS building footprints data in dense urban area

Sun, Yao and Wang, Yuanyuan and Zhu, Xiao Xiang (2019) Automatic registration of SAR image and GIS building footprints data in dense urban area. In: 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 927-930. IGARSS 2019, 28. Juli - 02. Aug. 2019, Yokohama, Japan. DOI: 10.1109/IGARSS.2019.8900187

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Official URL: https://ieeexplore.ieee.org/document/8900187

Abstract

In this paper, we propose a framework for the automatic registration of GIS building footprint polygons to a corresponding SAR image through the corresponding features of building walls in the two data. To extract feature lines, the Potts model is adopted for SAR image segmentation, and visibility test is performed on both data. The feature lines are then sampled to two point sets, and are registered using Iterative Closest Point (ICP) algorithm. The test result shows a registration accuracy of 0.67 m in azimuth direction, and 1.64m in range direction.

Item URL in elib:https://elib.dlr.de/128542/
Document Type:Conference or Workshop Item (Speech)
Title:Automatic registration of SAR image and GIS building footprints data in dense urban area
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sun, YaoYao.Sun (at) dlr.deUNSPECIFIED
Wang, YuanyuanYuanyuan.Wang (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:July 2019
Journal or Publication Title:2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2019.8900187
Page Range:pp. 927-930
Status:Published
Keywords:SAR, GIS building footprints, registration, urban area
Event Title:IGARSS 2019
Event Location:Yokohama, Japan
Event Type:international Conference
Event Dates:28. Juli - 02. Aug. 2019
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 > EO Data Science
Deposited By: Sun, Yao
Deposited On:06 Dec 2019 12:56
Last Modified:09 Dec 2019 09:53

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