Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data
DescriptionCosmology simulations are among some of the largest simulations being currently run on supercomputers, generating terabytes to petabytes of data for each run. Consequently, scientists are seeking to reduce the amount of storage needed while preserving enough quality for analysis and visualization of the data. One of the most commonly used visualization techniques for cosmology simulations is volume rendering. Here, we investigate how different types of lossy error-bound compression algorithms affect the quality of volume-rendered images generated from reconstructed datasets. We also compute a number of image quality assessment metrics to determine which ones are the most effective at identifying artifacts in the visualizations.
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TimeSunday, 13 November 202210:30am - 11am CST
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