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Attribute Profiles from Partitioning Trees

  • Petra Bosilj
  • Bharath Bhushan Damodaran
  • Erchan Aptoula
  • Mauro Dalla Mura
  • Sébastien Lefèvre
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10225)

Abstract

Morphological attribute profiles are among the most prominent spatial-spectral pixel description tools. They can be calculated efficiently from tree based representations of an image. Although widely and successfully used with various inclusion trees (i.e., component trees and tree of shape), in this paper, we investigate their implementation through partitioning trees, and specifically \(\alpha \)- and \((\omega )\)-trees. Our preliminary findings show that they are capable of comparable results to the state-of-the-art, while possessing additional properties rendering them suitable for the analysis of multivariate images.

Keywords

Attribute profiles Partitioning trees \(\alpha \)-tree \((\omega )\)-tree Hyperspectral images 

Notes

Acknowledgments

This work was supported by the French Agence Nationale de la Recherche (ANR) under reference ANR-13-JS02-0005-01 (Asterix project), by the BAGEP Award of the Science Academy and by the Turkish TUBITAK Grant 115E857.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Petra Bosilj
    • 1
    • 4
  • Bharath Bhushan Damodaran
    • 1
  • Erchan Aptoula
    • 2
  • Mauro Dalla Mura
    • 3
  • Sébastien Lefèvre
    • 1
  1. 1.Univ. Bretagne Sud - IRISAVannesFrance
  2. 2.Institute of Information TechnologiesGebze Technical UniversityGebzeTurkey
  3. 3.GIPSA Laboratory, Department Image and Signal, Grenoble-INPSaint Martin d’Heres CedexFrance
  4. 4.University of LincolnLincolnUK

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