Name
Abstract | ||
|---|---|---|
Segmentation is an essential ingredient in a wide range of image processing tasks and a building block of many visualization environ- ments. Many known segmentation techniques suer from being computationally exhaustive and thus decreasing interactivity, especially when considering volume data sets. Multilevel methods have proved to be a powerful ma- chinery to speed up applications which incor- porate some hierarchical structure. So does segmentation when considered on quadtree re- spectively octree data sets. Here we present a new approach which combines a discrete and a continuous multilevel segmentation model. In gure 1 four dierent |
Year | Venue | Keywords |
|---|---|---|
2000 | VMV | image processing |
Field | DocType | Citations |
Computer vision,Scale-space segmentation,Pattern recognition,Visualization,Computer science,Segmentation,Image processing,Smoothing,Artificial intelligence,Thresholding,Octree,Quadtree | Conference | 1 |
PageRank | References | Authors |
0.51 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marc Droske | 1 | 194 | 12.12 |
| T. Preußer | 2 | 65 | 7.76 |
| Martin Rumpf | 3 | 59 | 8.09 |