Towards a multi-device versión of the HYFMGPU Algorithm
| 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 | Fernández Fabeiro, Jorge | |
| dc.contributor.author | Ordóñez Iglesias, Álvaro | |
| dc.contributor.author | González Escribano, Arturo | |
| dc.contributor.author | Blanco Heras, Dora | |
| dc.date.accessioned | 2018-12-05T08:55:50Z | |
| dc.date.available | 2018-12-05T08:55:50Z | |
| dc.date.issued | 2018 | |
| dc.description | Proceedings of the 18th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2018, July 9–14, 2018 | gl |
| dc.description.abstract | The task consisting on estimating the translation, rotation and scaling of an image with respect to another take of the same scene obtained at different times, viewpoints and/or lightning conditions is known as image registration. Applications like environmental disasters management or rescue operations depend on real-time hyperspectral images registration, but most of the current FFT-based techniques ignore such performance needs. Ordóñez et al. proposed HYFMGPU [1], a single-GPU algorithm whose performance makes it suitable for real-time use cases. As hyperspectral sensors improve, both the size of images and the wavelength ranges covered are expected to increase, so that a multi-GPU implementation is proposed to satisfy such growing needs | gl |
| dc.description.sponsorship | This work has been partially supported by Regional Government of Castilla y León (Spain) and ERDF program of European Union: PROPHET project (JCYL-VA082P17) | gl |
| dc.identifier.citation | Fernández-Fabeiro, Jorge, Ordóñez, Álvaro, González-Escribano, Arturo, & B. Heras, Dora. (2018). Towards a Multi-device Version of the HYFMGPU Algorithm for Hyperspectral Scenes Registration. Zenodo. http://doi.org/10.5281/zenodo.1475157 | |
| dc.identifier.doi | 10.5281/zenodo.1475157 | |
| dc.identifier.isbn | 978-84-697-7861-6 | |
| dc.identifier.uri | http://hdl.handle.net/10347/17881 | |
| dc.language.iso | eng | gl |
| dc.publisher | International Conference on Computational and Mathematical Methods in Science and Engineering | gl |
| dc.relation.publisherversion | https://doi.org/10.5281/zenodo.1475157 | gl |
| dc.rights | © 2018 CMMSE. This work is under a Creative Commons License Attribution 4.0 International | gl |
| dc.rights | Atribución 4.0 Internacional | |
| dc.rights.accessRights | open access | gl |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Hyperspectral imaging | gl |
| dc.subject | Image registration | gl |
| dc.subject | Fourier transforms | gl |
| dc.subject | MultiGPU | gl |
| dc.subject | CUDA | gl |
| dc.subject | OpenMP | gl |
| dc.subject | Remote sensing | gl |
| dc.title | Towards a multi-device versión of the HYFMGPU Algorithm | gl |
| dc.type | book part | gl |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | a22a0ed8-b87b-473e-b16c-58d78c852dfd | |
| relation.isAuthorOfPublication | 24b7bf8f-61a5-44da-9a17-67fb85eab726 | |
| relation.isAuthorOfPublication.latestForDiscovery | a22a0ed8-b87b-473e-b16c-58d78c852dfd |
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