Title

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

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