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dc.contributor.authorVillalón-Turrubiates, Iván E.
dc.date.accessioned2016-04-21T19:21:56Z
dc.date.available2016-04-21T19:21:56Z
dc.date.issued2008
dc.identifier.citationIvan E. Villalon-Turrubiates, “Weighted Pixel Statistics for Multispectral Image Classification of Remote Sensing Signatures: Performance Study”, en Proceedings of the 5rd IEEE International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), Ciudad de México, 2008, pp. 534-539.es
dc.identifier.isbn978-1-4244-2498-6
dc.identifier.urihttp://hdl.handle.net/11117/3307
dc.descriptionThe extraction of remote sensing signatures from a particular geographical region allows the generation of electronic signature maps, which are the basis to create a high- resolution collection atlas processed in continuous discrete time. This can be achieved using a new multispectral image classification approach based on pixel statistics for the class description. This is referred to as the Weighted Pixel Statistics Method. This paper explores the effectiveness of this novel approach developed for supervised segmentation and classification of remote sensing signatures, with a comparison with the traditional Weighted Order Statistics Method. The extraction of remote sensing signatures from real-world high- resolution environmental remote sensing imagery is reported to probe the efficiency of the developed technique.es
dc.description.sponsorshipPrograma de Mejoramiento del Profesorado PROMEPes
dc.description.sponsorshipUniversidad de Guadalajaraes
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineerses
dc.relation.ispartofseriesIEEE International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE);5rd
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectImage Segmentationes
dc.subjectImage Classificationes
dc.subjectRemote Sensinges
dc.subjectStatisticses
dc.titleWeighted Pixel Statistics for Multispectral Image Classification of Remote Sensing Signatures: Performance Studyes
dc.typeinfo:eu-repo/semantics/conferencePaperes
rei.revisor5rd IEEE International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)
rei.peerreviewedYeses


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