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dc.contributor.author | Prades Nebot, José![]() |
es_ES |
dc.contributor.author | Salazar Afanador, Addisson![]() |
es_ES |
dc.contributor.author | Safont, Gonzalo![]() |
es_ES |
dc.contributor.author | Vergara Domínguez, Luís![]() |
es_ES |
dc.date.accessioned | 2022-12-14T11:47:01Z | |
dc.date.available | 2022-12-14T11:47:01Z | |
dc.date.issued | 2021-11-04 | es_ES |
dc.identifier.isbn | 978-1-6654-0179-1 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/190671 | |
dc.description.abstract | [EN] Estimation of the number of materials that are present in a hyperspectral image is a necessary step in many hyperspectral image processing algorithms, including classification and unmixing. Previously, we presented an algorithm that estimated the number of materials in the image using clustering principles. This algorithm is an iterative approach with two input parameters: the initial number of materials (P0) and the number of materials added in each iteration (¿). Since the choice of P0 and ¿ can have a large impact on the estimation accuracy. In this paper, we made an experimental study of the effect of these parameters on the algorithm performance. Thus, we show that the choice of a large ¿ can significantly reduce the estimation accuracy. These results can help to make an appropriate choice of these two parameters. | es_ES |
dc.description.sponsorship | This research has been supported by Generalitat Valenciana, grant PROMETEO 2019/109. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | IEEE | es_ES |
dc.relation.ispartof | Proceedings (ICARES 2021) | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Hyperspectral images | es_ES |
dc.subject | Endmembers | es_ES |
dc.subject | Clustering | es_ES |
dc.subject | Independent component analysis | es_ES |
dc.subject | Principal component analysis | es_ES |
dc.subject.classification | TEORIA DE LA SEÑAL Y COMUNICACIONES | es_ES |
dc.title | Experimental Study of Hierarchical Clustering for Unmixing of Hyperspectral Images | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.type | Capítulo de libro | es_ES |
dc.identifier.doi | 10.1109/ICARES53960.2021.9665201 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement///PROMETEO%2F2019%2F109//COMUNICACION Y COMPUTACION INTELIGENTES Y SOCIALES/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació | es_ES |
dc.description.bibliographicCitation | Prades Nebot, J.; Salazar Afanador, A.; Safont, G.; Vergara Domínguez, L. (2021). Experimental Study of Hierarchical Clustering for Unmixing of Hyperspectral Images. IEEE. 1-5. https://doi.org/10.1109/ICARES53960.2021.9665201 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES 2021) | es_ES |
dc.relation.conferencedate | Noviembre 03-04,2021 | es_ES |
dc.relation.conferenceplace | Online | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/ICARES53960.2021.9665201 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 5 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | S\462431 | es_ES |