Application-driven compression for visualizing large-scale time-varying data
Document Type
Article
Publication Date
1-1-2010
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. © 2010 IEEE.
Publication Title
IEEE Computer Graphics and Applications
Recommended Citation
Wang, C.,
Yu, H.,
&
Ma, K.
(2010).
Application-driven compression for visualizing large-scale time-varying data.
IEEE Computer Graphics and Applications,
30(1), 59-69.
http://doi.org/10.1109/MCG.2010.3
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10760