Visualizing Time-Varying Volume Data
Computing in Science and Engineering
Time-varying, multivariate volume data reduction
Proceedings of the 2005 ACM symposium on Applied computing
Hierarchical Clustering for Unstructured Volumetric Scalar Fields
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Wavelets for adaptively refined 3√2-subdivision meshes
International Journal of Computers and Applications
High quality rendering of compressed volume data formats
EUROVIS'05 Proceedings of the Seventh Joint Eurographics / IEEE VGTC conference on Visualization
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
Simultaneous classification of time-varying volume data based on the time histogram
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
A multiresolution volume rendering framework for large-scale time-varying data visualization
VG'05 Proceedings of the Fourth Eurographics / IEEE VGTC conference on Volume Graphics
VG'05 Proceedings of the Fourth Eurographics / IEEE VGTC conference on Volume Graphics
Volumetric reconstruction, compression and rendering of natural phenomena from multi-video data
VG'05 Proceedings of the Fourth Eurographics / IEEE VGTC conference on Volume Graphics
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Multiresolution methods for representing data at multiple levels of detail are widely used for large-scale two- and three-dimensional data sets. We present a four-dimensional multiresolution approach for time-varying volume data. This approach supports a hierarchy with spatial and temporal scalability.The hierarchical data organization is based on 4th-root-of-2 sub-division. The n-root-of-2-subdivision scheme only doubles the overall number of grid points in each subdivision step. This fact leads to fine granularity and high adaptivity, which is especially desirable in the spatial dimensions.For high-quality data approximation on each level of detail, we use quadrilinear B-spline wavelets. We present a linear B-spline wavelet lifting scheme based on n-root-of-2 subdivisionto obtain narrow masks for the update rules. Narrow masks provide a basis for out-of-core data exploration techniques and view-dependent visualization of sequences of time steps.