(The Eurographics Association, 2016) Luo, Shengzhou; Dingliana, John; Tobias Isenberg and Filip Sadlo
We present an automated technique to optimize the clarity of features in visualizations of 3D volume datasets. By adjusting the opacity transfer function, we achieve user-specified target distributions of feature conspicuity. Unlike previous techniques our approach accounts for both the issues of view-dependent occlusion and visual saliency of features in volume data. We demonstrate how the automated approach is useful in particular for optimizing the visualization of time-varying volume datasets.