A Statistical Direct Volume Rendering Framework for Visualization of Uncertain Data

@article{Sakhaee2017ASD,
  title={A Statistical Direct Volume Rendering Framework for Visualization of Uncertain Data},
  author={Elham Sakhaee and Alireza Entezari},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2017},
  volume={23},
  pages={2509-2520}
}
With uncertainty present in almost all modalities of data acquisition, reduction, transformation, and representation, there is a growing demand for mathematical analysis of uncertainty propagation in data processing pipelines. In this paper, we present a statistical framework for quantification of uncertainty and its propagation in the main stages of the visualization pipeline. We propose a novel generalization of Irwin-Hall distributions from the statistical viewpoint of splines and box… CONTINUE READING
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