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New hyperspectral data representation using binary partition tree
dc.contributor.author | Valero Valbuena, Silvia |
dc.contributor.author | Salembier Clairon, Philippe Jean |
dc.contributor.author | Chanussot, Jocelyn |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2011-01-13T11:10:57Z |
dc.date.available | 2011-01-13T11:10:57Z |
dc.date.created | 2010 |
dc.date.issued | 2010 |
dc.identifier.citation | Valero, S.; Salembier, P.; Chanussot, J. New hyperspectral data representation using binary partition tree. A: IEEE International Geoscience and Remote Sensing Symposium. "2010 IEEE International Geoscience and Remote Sensing Symposium". Honolulu: 2010, p. 80-83. |
dc.identifier.isbn | 978-1-4244-9564-1 |
dc.identifier.uri | http://hdl.handle.net/2117/11005 |
dc.description.abstract | The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. This paper introduces a new hierarchical structure representation for such images using binary partition trees (BPT). Based on region merging techniques using statistical measures, this region-based representation reduces the number of elementary primitives and allows a more robust filtering, segmentation, classification or information retrieval. To demonstrate BPT capabilites, we first discuss the construction of BPT in the specific framework of hyperspectral data. We then propose a pruning strategy in order to perform a classification. Labelling each BPT node with SVM classifiers outputs, a pruning decision based on an impurity measure is addressed. Experimental results on two different hyperspectral data sets have demonstrated the good performances of a BPT-based representation |
dc.format.extent | 4 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
dc.subject.lcsh | Binary Partition Tree |
dc.subject.lcsh | Support vector machines |
dc.subject.lcsh | Image processing |
dc.subject.lcsh | Signal theory (Telecommunication) |
dc.title | New hyperspectral data representation using binary partition tree |
dc.type | Conference report |
dc.subject.lemac | Senyal, Teoria del (Telecomunicació) |
dc.contributor.group | Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
dc.identifier.doi | 10.1109/IGARSS.2010.5649780 |
dc.description.awardwinning | Award-winning |
dc.rights.access | Open Access |
local.identifier.drac | 4498261 |
dc.description.version | Postprint (published version) |
local.citation.author | Valero, S.; Salembier, P.; Chanussot, J. |
local.citation.contributor | IEEE International Geoscience and Remote Sensing Symposium |
local.citation.pubplace | Honolulu |
local.citation.publicationName | 2010 IEEE International Geoscience and Remote Sensing Symposium |
local.citation.startingPage | 80 |
local.citation.endingPage | 83 |