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Processing multidimensional SAR and hyperspectral images with binary partition tree

Author
Alonso, A.; Valero, S.; Chanussot, J.; Lopez, C.; Salembier, P.
Type of activity
Journal article
Journal
Proceedings of the IEEE
Date of publication
2012-08-13
Volume
101
Number
3
First page
723
Last page
747
DOI
https://doi.org/10.1109/JPROC.2012.2205209 Open in new window
Repository
http://hdl.handle.net/2117/18321 Open in new window
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6266680 Open in new window
Abstract
The current increase of spatial as well as spectral resolutions of modern remote sensing sensors represents a real opportunity for many prac tical applications but also generates important challenges in terms of image processing. In particular, the spatial correlation between pixels and/or the spectral correlation between spectral bands of a given pixel cannot be ignored. The traditional pixel-based representation of images does not facilitate the handling of these correlations. In this paper, w...
Citation
Alonso, A. [et al.]. Processing multidimensional SAR and hyperspectral images with binary partition tree. "Proceedings of the IEEE", Març 2013, vol. 101, núm. 3, p. 723-747.
Keywords
Binary partition tree (BPT), classification, filtering, hyperspectral images, segmentation, synthetic aperture radar (SAR) images
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
RSLAB - Remote Sensing Lab

Participants