• DocumentCode
    177765
  • Title

    Multivalued Component-Tree Filtering

  • Author

    Kurtz, C. ; Naegel, B. ; Passat, N.

  • Author_Institution
    LIPADE, Univ. Paris Descartes, Paris, France
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    1008
  • Lastpage
    1013
  • Abstract
    We introduce the new notion of multivalued component-tree, that extends the classical component-tree initially devoted to grey-level images, in the mathematical morphology framework. We prove that multivalued component-trees can model images whose values are hierarchically organized. We also show that they can be efficiently built from standard component-tree construction algorithms, and involved in antiextensive filtering procedures. The relevance and usefulness of multivalued component-trees is illustrated by an applicative example on hierarchically classified remote sensing images.
  • Keywords
    filtering theory; geophysical image processing; image classification; mathematical morphology; remote sensing; trees (mathematics); component-tree construction algorithms; grey-level images; hierarchically classified remote sensing images; mathematical morphology; multivalued component-tree filtering; Computational efficiency; Image processing; Level set; Mathematical model; Morphology; Remote sensing; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.183
  • Filename
    6976893