Loading...
Loading...

Go to the content (press return)

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

Author
Alonso, A.; Lopez, C.; Salembier, P.; Valero, S.; Chanussot, J.
Type of activity
Presentation of work at congresses
Name of edition
Radar'2014
Date of publication
2014
Book of congress proceedings
International Radar Conference 2014: catching the invisible : 13-17 October 2014, Ille, France
Repository
http://hdl.handle.net/2117/26496 Open in new window
Abstract
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...
Citation
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.
Keywords
Binary Partition Tree, PolSAR, SAR, Speckle filtering
Group of research
CommSensLab-UPC - Centre Específic de Recerca en Comunicació i Detecció UPC
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
RSLAB - Remote Sensing Lab

Participants