Visualization of dynamic adaptive resolution scientific data

Andrew Foulks; R. Daniel Bergeron; Samuel H. Vohr

doi:10.1117/12.873025

24 January 2011 Visualization of dynamic adaptive resolution scientific data

Andrew Foulks, R. Daniel Bergeron, Samuel H. Vohr

Proceedings Volume 7868, Visualization and Data Analysis 2011; 78680E (2011) https://doi.org/10.1117/12.873025
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

Interactive visualization of very large data sets remains a challenging problem to the visualization community. One promising solution involves using adaptive resolution representations of the data. In this model, important regions of data are identified using reconstructive error analysis and are shown in higher detail. During the visualization, regions with higher error are rendered with high resolution data, while areas of low error are rendered at a lower resolution. We have developed a new dynamic adaptive resolution rendering algorithm along with software support libraries. These libraries are designed to extend the VisIt visualization environment by adding support for adaptive resolution data. VisIt supports domain decomposition of data, which we use to define our AR representation. We show that with this model, we achieve performance gains while maintaining error tolerances specified by the scientist.

Citation Download Citation

Andrew Foulks, R. Daniel Bergeron, and Samuel H. Vohr "Visualization of dynamic adaptive resolution scientific data", Proc. SPIE 7868, Visualization and Data Analysis 2011, 78680E (24 January 2011); https://doi.org/10.1117/12.873025

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