Issue No.01 - January/February (2010 vol.30)
Hongfeng Yu , Sandia National Laboratories
Chaoli Wang , Michigan Technological University
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2010.3
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.
large-data visualization, time-varying data visualization, importance-based compression, bit-wise texture packing, deferred filtering, computer graphics, graphics and multimedia
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