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

Authors:
Andrei C. Jalba;Michel A. Westenberg
Affiliations:
Department of Mathematics and Computer Science, Eindhoven University of Technology, MB Eindhoven, The Netherlands;Department of Mathematics and Computer Science, Eindhoven University of Technology, MB Eindhoven, The Netherlands
Venue:
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Year:
2011

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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.