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Multidimensional SAR data analysis based on binary partition trees and the covariance matrix geometry
Alonso González, Alberto; López Martínez, Carlos; Salembier Clairon, Philippe Jean; Valero Valbuena, Silvia; Chanussot, Jocelyn
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
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 convenient vehicle to exploit both the statistical properties, as well as the geometric properties of the multidimensional SAR data given by the covariance matrix. The BPT construction process and its exploitation for PolSAR and temporal data information estimation is analyzed in this work. In particular, this work focuses on the speckle noise filtering problem and the temporal characterization of the image dynamics. Results with real data are presented to illustrate the capabilities of the BPT processing approach, specially to maintain the spatial resolution and the small details of the image.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar
Syntethic aperture radar
SAR
PolSAR
Speckle filtering
Binary Partition Tree
Radar d'obertura sintètica
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