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dc.contributor.authorMarcello, Javier
dc.contributor.authorEugenio, Francisco Javier
dc.contributor.authorMarqués Acosta, Fernando
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2010-10-07T07:57:17Z
dc.date.available2010-10-07T07:57:17Z
dc.date.created2009
dc.date.issued2009
dc.identifier.citationMarcello, J.; Eugenio, F.; Marques, F. Cloud motion estimation in seviri image sequences. A: IEEE International Geoscience and Remote Sensing Symposium. "2009 IEEE International Geoscience and Remote Sensing Symposium". 2009, p. 642-645.
dc.identifier.isbn978-1-4244-3394-0
dc.identifier.urihttp://hdl.handle.net/2117/9492
dc.description.abstractDetermination of atmospheric dynamic characteristics from remote sensing imagery is fundamental in weather and climate studies. The SEVIRI radiometer, on board the MSG, with its 12 bands and 15 minutes sensing capability provides an important amount of information for cloud tracking. In this work, we have first conducted a detailed evaluation of twelve region matching techniques in order to select those providing the best results. For this performance evaluation, databases of synthetic and real sequences have been used. Next, the best metrics have been incorporated in a new methodology that includes a preliminary stage that segments cloudy structures to initialize the optimum motion estimation parameters (template size and search window dimensions). Also a study region mask is generated to disable the application of the motion estimation algorithm in unreliable areas, thus, eliminating erroneous vectors and decreasing the computation times.
dc.format.extent4 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshMeteosat (Artificial satellite)
dc.subject.lcshSignal theory (Telecommunication)
dc.subject.lcshAtmospheric temperature
dc.subject.lcshRemote sensing
dc.titleCloud motion estimation in seviri image sequences
dc.typeConference report
dc.subject.lemacSenyal, Teoria del (Telecomunicació)
dc.subject.lemacNúvols
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.identifier.doi10.1109/IGARSS.2009.5417842
dc.rights.accessOpen Access
local.identifier.drac3240566
dc.description.versionPostprint (published version)
local.citation.authorMarcello, J.; Eugenio, F.; Marques, F.
local.citation.contributorIEEE International Geoscience and Remote Sensing Symposium
local.citation.publicationName2009 IEEE International Geoscience and Remote Sensing Symposium
local.citation.startingPage642
local.citation.endingPage645


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