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dc.contributor.authorAlonso González, Alberto
dc.contributor.authorLópez Martínez, Carlos
dc.contributor.authorSalembier Clairon, Philippe Jean
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2012-09-27T15:38:31Z
dc.date.created2012-02
dc.date.issued2012-02
dc.identifier.citationAlonso, A.; López, C.; Salembier, P. Filtering and segmentation of polarimetric SAR data based on binary partition trees. "IEEE transactions on geoscience and remote sensing", Febrer 2012, vol. 50, núm. 2, p. 593-605.
dc.identifier.issn0196-2892
dc.identifier.urihttp://hdl.handle.net/2117/16589
dc.description.abstractIn this paper,we propose the use of binary partition trees (BPT) to introduce a novel region-based and multi-scale polarimetric SAR (PolSAR) data representation. The BPT structure represents homogeneous regions in the data at different detail levels. The construction process of the BPT is based, firstly, on a region model able to represent the homogeneous areas, and, secondly, on a dissimilarity measure in order to identify similar areas and define the merging sequence. Depending on the final application, a BPT pruning strategy needs to be introduced. In this paper, we focus on the application of BPT PolSAR data representation for speckle noise filtering and data segmentation on the basis of the Gaussian hypothesis, where the average covariance or coherency matrices are considered as a region model. We introduce and quantitatively analyze different dissimilarity measures. In this case, and with the objective to be sensitive to the complete polarimetric information under the Gaussian hypothesis, dissimilarity measures considering the complete covariance or coherency matrices are employed.When confronted to PolSAR speckle filtering, two pruning strategies are detailed and evaluated. As presented, the BPT PolSAR speckle filter defined filters data according to the complete polarimetric information. As shown, this novel filtering approach is able to achieve very strong filtering while preserving the spatial resolution and the polarimetric information. Finally, the BPT representation structure is employed for high spatial resolution image segmentation applied to coastline detection. The analyses detailed in this work are based on simulated, as well as on real PolSAR data acquired by the ESAR system of DLR and the RADARSAT-2 system.
dc.format.extent13 p.
dc.language.isoeng
dc.publisherIEEE Press. Institute of Electrical and Electronics Engineers
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció
dc.subject.lcshSynthetic aperture radar
dc.subject.lcshRadar
dc.titleFiltering and segmentation of polarimetric SAR data based on binary partition trees
dc.typeArticle
dc.subject.lemacRadar d'obertura sintètica
dc.subject.lemacRadar
dc.contributor.groupUniversitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.identifier.doi10.1109/TGRS.2011.2160647
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5971780
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac9493993
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorAlonso, A.; López, C.; Salembier, P.
local.citation.publicationNameIEEE transactions on geoscience and remote sensing
local.citation.volume50
local.citation.number2
local.citation.startingPage593
local.citation.endingPage605


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