Transmittance-based Extinction and Viewpoint Optimization
Computer Graphics Forum (Proc. EuroVis) 2024
Friedrich-Alexander-Universität Erlangen-Nürnberg
Abstract
A long-standing challenge in volume visualization is the effective communication of relevant spatial structures that might be hidden due to occlusions. Given a scalar field that indicates the importance of every point in the domain, previous work synthesized volume visualizations by weighted averaging of samples along view rays or by optimizing a spatially-varying extinction field through an energy minimization. This energy minimization, however, did not directly measure the contribution of an individual sample to the final pixel color. In this paper, we measure the visibility of relevant structures directly by incorporating the transmittance into a non-linear energy minimization. For the first time, we not only perform a transmittance-based extinction optimization, we concurrently optimize the camera position to find ideal viewpoints. We derive the partial derivatives for the gradient-based optimization symbolically, which makes the application of automatic differentiation methods unnecessary. The transmittance-based formulation gives a direct visibility measure that is communicated to the user in order to make aware of potentially overlooked relevant structures. Our approach is compatible with any measure of importance and its versatility is demonstrated in multiple data sets.
Video
Interactive
An interactive comparison of extinction optimization methods on the EARTH MANTLE, VISIBLE HUMAN, HEPTANE FLAME, and ROTATING MIXER data set. Viola et al. [VKG04] and Marchesin et al. [MMD10] did not include shadow optimizations and are therefore compared without shadowing. In addition, Ament et al. [AZD17] with and without shadowing were compared with our method. Previous approaches ([VKG04],[MMD10]) provide limited depth perception. Ament et al. [AZD17] has global parameters, making it difficult to bring out differently important structures throughout the domain. Some parts might even be lost entirely. In contrast, our method maximizes the visibility successfully everywhere.
BibTeX
@article{Himmler24EuroVis,
author = {Himmler, Paul and G{\"u}nther, Tobias},
title = {Transmittance-based Extinction and Viewpoint Optimization},
journal = {Computer Graphics Forum (Eurographics Conference on Visualization)},
volume = {43},
number = {3},
year = {2024},
publisher = {Eurographics},
address = {Odense, Denmark},
}
Acknowledgements
We thank Gábor Janiga from the University of Magdeburg for providing the ROTATING MIXER. The EARTH MANTLE was simulated by Anna Gülcher from the NASA Jet Propulsion Laboratory. The VISIBLE HUMAN data set was provided by Peter Ratiu via The National Library of Medicine, Bethesda, MD. The HEPTANE FLAME data set was released by the University of Utah Center for the Simulation of Accidental Fires and Explosions. This work was supported by DFG grant no. GU 945/3-1.