Sciweavers

VIS
2007
IEEE

Multifield Visualization Using Local Statistical Complexity

14 years 4 months ago
Multifield Visualization Using Local Statistical Complexity
Modern unsteady (multi-)field visualizations require an effective reduction of the data to be displayed. From a huge amount of information the most informative parts have to be extracted. Instead of the fuzzy application dependent notion of feature, a new approach based on information theoretic concepts is introduced in this paper to detect important regions. This is accomplished by extending the concept of local statistical complexity from finite state cellular automata to discretized (multi-)fields. Thus, informative parts of the data can be highlighted in an application-independent, purely mathematical sense. The new measure can be applied to unsteady multifields on regular grids in any application domain. The ability to detect and visualize important parts is demonstrated using diffusion, flow, and weather simulations.
Heike Jänicke, Alexander Wiebel, Gerik Scheuerm
Added 03 Nov 2009
Updated 03 Nov 2009
Type Conference
Year 2007
Where VIS
Authors Heike Jänicke, Alexander Wiebel, Gerik Scheuermann, Wolfgang Kollmann
Comments (0)