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2017-07-01Zeitschriftenartikel DOI: 10.3390/rs9070676
AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data
dc.contributor.authorScheffler, Daniel
dc.contributor.authorHollstein, André
dc.contributor.authorDiedrich, Hannes
dc.contributor.authorSegl, Karl
dc.contributor.authorHostert, Patrick
dc.date.accessioned2019-08-06T10:41:28Z
dc.date.available2019-08-06T10:41:28Z
dc.date.issued2017-07-01none
dc.date.updated2019-07-31T13:36:46Z
dc.identifier.urihttp://edoc.hu-berlin.de/18452/21118
dc.description.abstractAbstract Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal data. In recent decades, many algorithms have been developed to enable manual, semi- or fully automatic displacement correction. Especially in the context of big data processing and the development of automated processing chains that aim to be applicable to different remote sensing systems, there is a strong need for efficient, accurate and generally usable co-registration. Here, we present AROSICS (Automated and Robust Open-Source Image Co-Registration Software), a Python-based open-source software including an easy-to-use user interface for automatic detection and correction of sub-pixel misalignments between various remote sensing datasets. It is independent of spatial or spectral characteristics and robust against high degrees of cloud coverage and spectral and temporal land cover dynamics. The co-registration is based on phase correlation for sub-pixel shift estimation in the frequency domain utilizing the Fourier shift theorem in a moving-window manner. A dense grid of spatial shift vectors can be created and automatically filtered by combining various validation and quality estimation metrics. Additionally, the software supports the masking of, e.g., clouds and cloud shadows to exclude such areas from spatial shift detection. The software has been tested on more than 9000 satellite images acquired by different sensors. The results are evaluated exemplarily for two inter-sensoral and two intra-sensoral use cases and show registration results in the sub-pixel range with root mean square error fits around 0.3 pixels and better.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectimage co-registrationeng
dc.subjectPythoneng
dc.subjectsub-pixeleng
dc.subjectFourier shift theoremeng
dc.subjectopticaleng
dc.subjectradareng
dc.subjectphase correlationeng
dc.subjectgeometric pre-processingeng
dc.subjectinter-sensoreng
dc.subjectintra-sensoreng
dc.subject.ddc620 Ingenieurwissenschaften und zugeordnete Tätigkeitennone
dc.titleAROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Datanone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/21118-3
dc.identifier.doi10.3390/rs9070676none
dc.identifier.doihttp://dx.doi.org/10.18452/20364
dc.type.versionpublishedVersionnone
local.edoc.container-titleRemote Sensingnone
local.edoc.pages21none
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameMDPInone
local.edoc.container-publisher-placeBaselnone
local.edoc.container-volume9none
local.edoc.container-issue7none
local.edoc.container-firstpage676/1none
local.edoc.container-lastpage676/21none
dc.description.versionPeer Reviewednone
dc.identifier.eissn2072-4292
local.edoc.affiliationScheffler, Daniel; Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Section Remote Sensing, Telegrafenberg, 14473 Potsdam, Germany, Geography Department, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany,none
local.edoc.affiliationHollstein, André; Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Section Remote Sensing, Telegrafenberg, 14473 Potsdam, Germany,none
local.edoc.affiliationDiedrich, Hannes; Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Section Remote Sensing, Telegrafenberg, 14473 Potsdam, Germany,none
local.edoc.affiliationSegl, Karl; Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Section Remote Sensing, Telegrafenberg, 14473 Potsdam, Germany,none
local.edoc.affiliationHostert, Patrick; Geography Department, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany, Integrated Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany,none

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