Immersive 3D flow visualization based on enhanced texture convolution and volume rendering

Jin Guo; Cui Xie

doi:10.1117/12.2625857

30 April 2022 Immersive 3D flow visualization based on enhanced texture convolution and volume rendering

Jin Guo, Cui Xie

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121772T (2022) https://doi.org/10.1117/12.2625857
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

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.

Citation Download Citation

Jin Guo and Cui Xie "Immersive 3D flow visualization based on enhanced texture convolution and volume rendering", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121772T (30 April 2022); https://doi.org/10.1117/12.2625857

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