A comparison of two tree representations for data-driven volumetric image filtering

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Abstract

We compare two tree-based, hierarchical representations of volumetric gray-scale images for data-driven image filtering. One representation is the max-tree, in which tree nodes represent connected components of all level sets of a data set. The other representation is the watershed tree, consisting of nodes representing nested, homogeneous image regions. Region attribute-based filtering is achieved by pruning the trees. Visualization is used to compare both the filtered images and trees. In our comparison, we also consider flexibility, intuitiveness, and extendability of both tree representations.
Original languageEnglish
Title of host publicationMathematical Morphology and Its Applications to Image and Signal Processing (10th International Symposium, ISMM 2011, Verbania-Intra, Italy, July 6-8, 2011. Proceedings)
EditorsP. Soille, M. Pesaresi, G.K. Ouzounis
Place of PublicationBerlin
PublisherSpringer
Pages405-416
ISBN (Print)978-3-642-21568-1
DOIs
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science
Volume6671
ISSN (Print)0302-9743

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