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Hyperspectral image segmentation using binary partition trees

Author
Valero, S.; Salembier, P.; Chanussot, J.
Type of activity
Presentation of work at congresses
Name of edition
ICIP 2011
Date of publication
2011
Presentation's date
2011-09-12
Book of congress proceedings
Image Processing (ICIP), 2011 18th IEEE International Conference on
First page
1273
Last page
1276
Publisher
IEEE
DOI
https://doi.org/10.1109/ICIP.2011.6115666 Open in new window
Repository
http://hdl.handle.net/2117/14622 Open in new window
URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6094293 Open in new window
Abstract
The work presented here proposes a new Binary Partition Tree pruning strategy aimed at the segmentation of hyperspectral images. The BPT is a region-based representation of images that involves a reduced number of elementary primitives and therefore allows to design a robust and efficient segmentation algorithm. Here, the regions contained in the BPT branches are studied by recursive spectral graph partitioning. The goal is to remove subtrees composed of nodes which are considered to be similar....
Citation
Valero, S.; Salembier, P.; Chanussot, J. Hyperspectral image segmentation using binary partition trees. A: IEEE International Conference on Image Processing. "Image Processing (ICIP), 2011 18th IEEE International Conference on". Bruselas: IEEE, 2011, p. 1273-1276.
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

  • Valero Valbuena, Silvia  (author and speaker )
  • Salembier Clairon, Philippe  (author and speaker )
  • Chanussot, Jocelyn  (author and speaker )