Fourier–Mellin registration of two hyperspectral images
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías da Información | gl |
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Departamento de Electrónica e Computación | gl |
| dc.contributor.area | Área de Enxeñaría e Arquitectura | |
| dc.contributor.author | Ordóñez Iglesias, Álvaro | |
| dc.contributor.author | Argüello Pedreira, Francisco | |
| dc.contributor.author | Blanco Heras, Dora | |
| dc.date.accessioned | 2018-12-05T08:22:22Z | |
| dc.date.available | 2018-12-05T08:22:22Z | |
| dc.date.issued | 2017-03-21 | |
| dc.description.abstract | Hyperspectral images contain a great amount of information which can be used to more robustly register such images. In this article, we present a phase correlation method to register two hyperspectral images that takes into account their multiband structure. The proposed method is based on principal component analysis, the multilayer fractional Fourier transform, a combination of log-polar maps, and peak processing. The combination of maps is aimed at highlighting some peaks in the log-polar map using information from different bands. The method is robust and has been successfully tested for any rotation angle with commonly used hyperspectral scenes in remote sensing for scales of up to 7.5× and with pairs of hyperspectral images taken on different dates by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor for scales of up to 6.0× | gl |
| dc.description.peerreviewed | SI | gl |
| dc.description.sponsorship | This work was supported in part by the Consellería de Cultura, Educación e Ordenación Universitaria [grant numbers GRC2014/008 and ED431G/08] and Ministry of Education, Culture and Sport, Government of Spain [grant numbers TIN2013-41129-P and TIN2016-76373-P] both are co-funded by the European Regional Development Fund (ERDF) | gl |
| dc.identifier.citation | Ordóñez, Á., Argüello, F., & Heras, D. (2017). Fourier–Mellin registration of two hyperspectral images. International Journal Of Remote Sensing, 38(11), 3253-3273. doi: 10.1080/01431161.2017.1292071 | gl |
| dc.identifier.doi | 10.1080/01431161.2017.1292071 | |
| dc.identifier.essn | 1366-5901 | |
| dc.identifier.issn | 0143-1161 | |
| dc.identifier.uri | http://hdl.handle.net/10347/17879 | |
| dc.language.iso | eng | gl |
| dc.publisher | Taylor & Francis | gl |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2013-41129-P/ES/SOLUCIONES HARDWARE Y SOFTWARE PARA LA COMPUTACION DE ALTAS PRESTACIONES | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2016-76373-P/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1080/01431161.2017.1292071 | gl |
| dc.rights | © 2017 Taylor & Francis Group, LLC | gl |
| dc.rights.accessRights | open access | gl |
| dc.subject | Hyperspectral data | gl |
| dc.subject | Image registration | gl |
| dc.subject | Fourier transform | gl |
| dc.subject | Feature extraction | gl |
| dc.subject | Remote sensing | gl |
| dc.title | Fourier–Mellin registration of two hyperspectral images | gl |
| dc.type | journal article | gl |
| dc.type.hasVersion | AM | gl |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | a22a0ed8-b87b-473e-b16c-58d78c852dfd | |
| relation.isAuthorOfPublication | 01d58a96-54b8-492d-986c-f9005bac259c | |
| relation.isAuthorOfPublication | 24b7bf8f-61a5-44da-9a17-67fb85eab726 | |
| relation.isAuthorOfPublication.latestForDiscovery | a22a0ed8-b87b-473e-b16c-58d78c852dfd |
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