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Mathematical Methods Applied to the Representation and Visualization of Large Scientific Data Sets
Student-Run Research Seminar| Speaker: | Bernd Hamann, UC Davis |
| Location: | 693 Kerr |
| Start time: | Wed, Oct 19 2005, 12:10PM |
Established data compression and multiresolution techniques are an essential part of the processing and exploration of massive scientific data sets. Most existing techniques, especially wavelet-based approaches, assume that data sets to be represented hierarchically are defined on rather regular underlying mesh structures. This talk is aimed at pointing out some directions for establishing wavelet-based multiresolution methods for scientific data sets whose underlying mesh structure is much less restrictive. The possible directions that are illumed to are based on concepts from approximation and spline theory, computational geometry, and optimization. Further, a close coupling between driving application domains and supporting data approximation and visualization technology is emphasized.