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