Multimodal Probabilistic Latent Semantic Analysis for Sentinel-1 and Sentinel-2 Image Fusion
Visualitza/
Impacte
Scholar |
Altres documents de l'autoria: Fernandez-Beltran, Ruben; Haut, Juan M.; Paoletti, Mercedes Eugenia; Plaza, Javier; Plaza, Antonio; Pla, Filiberto
Metadades
Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
comunitat-uji-handle4:
INVESTIGACIONMetadades
Títol
Multimodal Probabilistic Latent Semantic Analysis for Sentinel-1 and Sentinel-2 Image FusionAutoria
Data de publicació
2018-09Editor
IEEECita bibliogràfica
FERNANDEZ-BELTRAN, Ruben, et al. Multimodal Probabilistic Latent Semantic Analysis for Sentinel-1 and Sentinel-2 Image Fusion. IEEE Geoscience and Remote Sensing Letters, 2018, 15.9: 1347-1351.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://ieeexplore.ieee.org/abstract/document/8392415Versió
info:eu-repo/semantics/submittedVersionParaules clau / Matèries
Resum
Probabilistic topic models have recently shown a great potential in the remote sensing image fusion field, which is particularly helpful in land-cover categorization tasks. This letter first studies the application ... [+]
Probabilistic topic models have recently shown a great potential in the remote sensing image fusion field, which is particularly helpful in land-cover categorization tasks. This letter first studies the application of probabilistic latent semantic analysis (pLSA) and latent Dirichlet allocation to remote sensing synthetic aperture radar (SAR) and multispectral imaging (MSI) unsupervised land-cover categorization. Then, a novel pLSA-based image fusion approach is presented, which pursues to uncover multimodal feature patterns from SAR and MSI data in order to effectively fuse and categorize Sentinel-1 and Sentinel-2 remotely sensed data. Experiments conducted over two different data sets reveal the advantages of the proposed approach for unsupervised land-cover categorization tasks. [-]
Proyecto de investigación
Generalitat Valenciana (APOSTD/2017/007) ; Spanish Ministry (FPU14/02012- FPU15/02090, ESP2016-79503-C2-2-P) ; Junta de Extremadura (GR15005).Drets d'accés
© Copyright 2018 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
Apareix a les col.leccions
- INIT_Articles [754]