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
Link To Document :
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