Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/40295
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dc.contributor.authorIbarrola-Ulzurrun, E.en_US
dc.contributor.authorMarcello, Javieren_US
dc.contributor.authorGonzalo-Martin, Consueloen_US
dc.date.accessioned2018-06-11T09:24:35Z-
dc.date.available2018-06-11T09:24:35Z-
dc.date.issued2017en_US
dc.identifier.isbn9781510613188
dc.identifier.issn0277-786Xen_US
dc.identifier.urihttp://hdl.handle.net/10553/40295-
dc.description.abstractThe hyperspectral imagery is formed by a several narrow and continuous bands covering different regions of the electromagnetic spectrum, such as spectral bands of the visible, near infrared and far infrared. Hyperspectral imagery provides extremely higher spectral resolution than high spatial resolution multispectral imagery, improving the detection capability of terrestrial objects. The greatest difficulty found in the hyperspectral processing is the high dimensionality of these data, which brings out the 'Hughes' phenomenon. This phenomenon specifies that the size of training set required for a given classification increases exponentially with the number of spectral bands. Therefore, the dimensionality of the hyperspectral data is an important drawback when applying traditional classification or pattern recognition approaches to this hyperspectral imagery. In our context, the dimensionality reduction is necessary to obtain accurate thematic maps of natural protected areas. Dimensionality reduction can be divided into the feature-selection algorithms and featureextraction algorithms. We focus the study in the feature-extraction algorithms like Principal Component Analysis (PCA), Minimum Noise Fraction (MNF) and Independent Component Analysis (ICA). After a review of the state-of-Art, it has been observed a lack of a comparative study on the techniques used in the hyperspectral imagery dimensionality reduction. In this context, our objective was to perform a comparative study of the traditional techniques of dimensionality reduction (PCA, MNF and ICA) to evaluate their performance in the classification of high spatial resolution imagery of the CASI (Compact Airborne Spectrographic Imager) sensor.en_US
dc.languageengen_US
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineeringen_US
dc.sourceProceedings of SPIE - The International Society for Optical Engineering [ISSN 0277-786X], v. 10427, article number 2278501en_US
dc.subject250616 Teledetección (Geología)en_US
dc.subject220921 Espectroscopiaen_US
dc.subject.otherAlgorithms
dc.titleEvaluation of dimensionality reduction techniques in hyperspectral imagery and their application for the classification of terrestrial ecosystemsen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.relation.conferenceConference on Image and Signal Processing for Remote Sensing XXIII
dc.relation.conferenceImage and Signal Processing for Remote Sensing XXIII 2017
dc.identifier.doi10.1117/12.2278501
dc.identifier.scopus85041018130
dc.identifier.isi000425842500012-
dc.contributor.authorscopusid57193098496
dc.contributor.authorscopusid6602158797
dc.contributor.authorscopusid36561411500
dc.relation.volume10427-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid5530081
dc.contributor.daisngid702897
dc.contributor.daisngid1398100
dc.contributor.wosstandardWOS:Ibarrola-Ulzurrun, E
dc.contributor.wosstandardWOS:Marcello, J
dc.contributor.wosstandardWOS:Gonzalo-Martin, C
dc.date.coverdateEnero 2017
dc.identifier.conferenceidevents121084
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.event.eventsstartdate11-09-2017-
crisitem.event.eventsstartdate11-09-2017-
crisitem.event.eventsenddate13-09-2017-
crisitem.event.eventsenddate13-09-2017-
crisitem.author.deptGIR IOCAG: Procesado de Imágenes y Teledetección-
crisitem.author.deptIU de Oceanografía y Cambio Global-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0001-5062-7491-
crisitem.author.orcid0000-0002-9646-1017-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.fullNameIbarrola Ulzurrun, Edurne-
crisitem.author.fullNameMarcello Ruiz, Francisco Javier-
Colección:Actas de congresos
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