Application-driven compression for visualizing large-scale time-varying data

Chaoli Wang, Hongfeng Yu, Kwan Liu Ma

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


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.

Original languageEnglish (US)
Article number5370743
Pages (from-to)59-69
Number of pages11
JournalIEEE Computer Graphics and Applications
Issue number1
StatePublished - Jan 2010
Externally publishedYes


  • Bit-wise texture packing
  • Computer graphics
  • Deferred filtering
  • Graphics and multimedia
  • Importance-based compression
  • Large-data visualization
  • Time-varying data visualization

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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