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Object-related alignment of heterogeneous image data in remote sensing

Auer, Stefan and Schmitt, Michael and Reinartz, Peter (2018) Object-related alignment of heterogeneous image data in remote sensing. IEEE. FUSION 2018, 11.-13. Juli 2018, Cambridge.

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Official URL: https://fusion2018.eng.cam.ac.uk/

Abstract

The fusion of heterogeneous image data, in particular optical images and synthetic aperture radar (SAR) images, is highly worthwhile in the context of remote sensing tasks as it allows to exploit complementary information - such as spectral and distance measurements or different observation perspectives - of the two data sources while diminishing their individual weaknesses (e.g. cloud cover, difficulty of image interpretation, limited sensor revisit). However, relating the heterogeneous data on the signal level requires a data alignment step, which cannot be realized without auxiliary knowledge. This paper addresses and discusses this fundamental fusion problem in remote sensing in the context of a framework named SimGeoI, which solves the multi-sensor alignment task based on geometric knowledge from existing digital surface models. Sections of optical and SAR images are related to individual objects using interpretation layers generated with ray tracing techniques. Results of SimGeoI are presented for a test site in London in order to motivate an object-related fusion of remote sensing images.

Item URL in elib:https://elib.dlr.de/120229/
Document Type:Conference or Workshop Item (Speech)
Title:Object-related alignment of heterogeneous image data in remote sensing
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Auer, StefanStefan.Auer (at) dlr.dehttps://orcid.org/0000-0001-9310-2337
Schmitt, Michaelm.schmitt (at) tum.deUNSPECIFIED
Reinartz, Peterpeter.reinartz (at) dlr.dehttps://orcid.org/0000-0002-8122-1475
Date:July 2018
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-8
Publisher:IEEE
Status:Published
Keywords:Remote sensing, data fusion, optical data, SAR data, simulation
Event Title:FUSION 2018
Event Location:Cambridge
Event Type:international Conference
Event Dates:11.-13. Juli 2018
Organizer:IEEE
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 > Photogrammetry and Image Analysis
Deposited By: Auer, Dr. Stefan
Deposited On:04 Jun 2018 10:08
Last Modified:31 Jul 2019 20:17

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