The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - January/February (2010 vol.30)
pp: 59-69
Hongfeng Yu , Sandia National Laboratories
Chaoli Wang , Michigan Technological University
ABSTRACT
The authors present an application-driven approach to compressing large-scale time-varying volume data. Their approach identifies a reference feature to partition the data into space-time blocks, which are compressed with various precisions depending on their association to the feature. Runtime decompression is performed with bit-wise texture packing and deferred filtering. This method achieves high compression rates and interactive rendering while preserving fine details surrounding regions of interest. Such an application-driven approach could help computational scientists cope with the large-data problem.
INDEX TERMS
large-data visualization, time-varying data visualization, importance-based compression, bit-wise texture packing, deferred filtering, computer graphics, graphics and multimedia
CITATION
Hongfeng Yu, Chaoli Wang, "Application-Driven Compression for Visualizing Large-Scale Time-Varying Data", IEEE Computer Graphics and Applications, vol.30, no. 1, pp. 59-69, January/February 2010, doi:10.1109/MCG.2010.3
REFERENCES
1. M.W. Jones, J.A. Bærentzen, and M. Srámek, "3D Distance Fields: A Survey of Techniques and Applications," IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 4, 2006, pp. 581–599.
2. A.E. Shortt, T.J. Naughton, and B. Javidi, "Histogram Approaches for Lossy Compression of Digital Holograms of Three-Dimensional Objects," IEEE Trans. Image Processing, vol. 16, no. 6, 2007, pp. 1548–1556.
3. N. Fout et al., "High-Quality Rendering of Compressed Volume Data Formats," Proc. Eurographics/IEEE VGTC Symp. Visualization, Eurographics Assoc., 2005, pp. 77–84.
4. I. Viola, A. Kanitsar, and M.E. Gröller, "Importance-Driven Volume Rendering," Proc. IEEE Visualization Conf., IEEE CS Press, 2004, pp. 139–145.
17 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool