Immersive 3D flow visualization based on enhanced texture convolution and volume rendering
Jin Guo, Cui Xie · International Workshop on Advanced Imaging Technology (IWAIT) 2022 · 2022
In this paper, we proposed a texture-based 3D flow visualization method in an immersive environment. The algorithm uses line integral convolution to display the directional information of the flow fields. The algorithm enhances the contrast between streamlines by injecting a certain percentage of random noise into the convolution-generated texture. We introduce a high-pass filtering process to improve the quality of enhanced rendered texture further. In addition, this paper designs a volume rendering transfer function for the immersive environment, which can effectively extract the significant features of the flow field in the immersive environment and highlight the features areas of interest to users.