Publications

Optimization of Color and Visibility for Dense Line Sets

Berkan Tuncay and Tobias Günther

Vision, Modeling and Visualization (VMV), 2024

Abstract

In flow visualization, the depiction of line geometry in three-dimensional domains is often accompanied by occlusions. If there is a notion of which geometry is important to see, then a careful adjustment of the transparency is possible to ensure that irrelevant geometry is not occluding the meaningful structures, which is an inherently view-dependent problem. Past work in this line of research focused on the view-dependent adjustment of the transparency only and left the color channel open for the encoding of additional information. For a given viewpoint, the colormap could be set by the user, but once the view changes, the visible geometry is different and the colormap might no longer be utilizing its full color range. Thus, in this paper, we readjust the color transfer function to the new view, such that the colors of the colormap are utilized uniformly in the final image. To this end, a visibility histogram of all scalar values is recalculated and equalized on the GPU each frame. Further, past approaches required a set of lines that is not too dense, since the opacity optimization would otherwise fade out all lines similarly. For this reason, we incorporate a hierarchical line clustering for which we experimentally study the influence of distance metrics, linkage options, and representative choices. We apply the method in a number of scientific data sets, including examples from atmospheric sciences, aerodynamics, and electromagnetism.

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