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Interactive Visualization of Function Fields by Range-Space Segmentation

  • Author(s): Anderson, John C.
  • Gosink, Luke
  • Duchaineau, Mark A.
  • Joy, Ken
  • et al.
Abstract

We present a dimension reduction and feature extraction method for the visualization and analysis of function field data. Function fields are a class of high-dimensional, multi-variate data in which data samples are one-dimensional scalar functions. Our approach focuses upon the creation of high-dimensional range-space segmentations, from which we can generate meaningful visualizations and extract separating surfaces between features. We demonstrate our approach on high-dimensional spectral imagery, and particulate pollution data from air quality simulations.

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