maximize


@inproceedings{DrPrRu00,
  author = {Droske, M. and Preu{\ss}er, T. and Rumpf, M.},
  title = {A Multilevel Segmentation Method},
  booktitle = {Vision, Modeling and Visualization},
  year = {2000},
  editor = {Girod, B. and Greiner, G. and Niemann, H. and Seidel, H.-P.},
  pages = {327--336},
  abstract = {Segmentation is an essential ingredient in a wide range of image processing
	tasks and a building block of many visualization environments. Many
	known segmentation techniques suffer from being computationally exhaustive
	and thus decreasing interactivity, especially when considering volume
	data sets. Multilevel methods have proved to be a powerful machinery
	to speed up applications which incorporate some hierarchical structure.
	So does segmentation when considered on quadtree respectively octree
	data sets. Here we present a new approach which combines a discrete
	and a continuous multilevel segmentation model. At first, the discrete
	method enables a fast segmentation depending on possibly multiple
	parameters describing the segment boundary and on selected seed points
	inside a segment. In an interactive process the user is able to ajust
	seed points which steer the automatic discrete segmentation process.
	Furthermore fast multilevel splatting techniques simultaneously enable
	interactive frame rates in the visualization to validate the obtained
	results. Thus, the user is effectively supported in the selection
	of appropriate parameters for the segmentation. Once an acceptable
	voxel discrete approximation is found a second segmentation and smoothing
	method based on a continuous model comes into play. It can be regarded
	as an suitable postprocessing step. Hence, solving an appropriate
	diffusion problem the boundary approximation of the already obtained
	segment is improved including a suitable tangential smoothing.},
  pdf = {http://numod.ins.uni-bonn.de/research/papers/public/DrPrRu00.pdf 1}
}