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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 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 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 Postprint (published version) 2014 Conference report 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. 978-1-4799-4195-7 https://hdl.handle.net/2117/26496 10.1109/RADAR.2014.7060431 eng https://ieeexplore.ieee.org/abstract/document/7060431 Restricted access - publisher's policy 6 p. application/pdf Institute of Electrical and Electronics Engineers (IEEE)