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Multidimensional SAR data analysis based on binary partition trees and the covariance matrix geometry

Autor
Alonso, A.; Lopez, C.; Salembier, P.; Valero, S.; Chanussot, J.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
Radar'2014
Any de l'edició
2014
Llibre d'actes
International Radar Conference 2014: catching the invisible : 13-17 October 2014, Ille, France
Repositori
http://hdl.handle.net/2117/26496 Obrir en finestra nova
Resum
In this paper, we propose the use of the Binary Partition Tree (BPT) as a region-based and multi-scale image representation to process multidimensional SAR data, with special emphasis on polarimetric SAR data. We also show that this approach could be extended to other types of remote sensing imaging technologies, such as hyperspatial imagery. The Binary Partition Tree contains a lot of information about the image structure at different detail levels. At the same time, this structure represents a...
Citació
Alonso, A. [et al.]. Multidimensional SAR data analysis based on binary partition trees and the covariance matrix geometry. A: International Radar Conference. "International Radar Conference 2014: catching the invisible : 13-17 October 2014, Ille, France". Lille: 2014.
Paraules clau
Sar, Polsar, Speckle Filtering, Binary Partition Tree
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
RSLAB - Grup de Recerca en Teledetecció

Participants