Dynamic visual simulation of marine vector field based on LIC—a case study of surface wave field in typhoon condition
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Line integral convolution (LIC) is a useful visualization technique for a vector field. However, the output image produced by LIC has many problems in a marine vector field. We focus on the visual quality improvement when LIC is applied in the ocean steady and unsteady flow field in the following aspects. When a white noise is used as the input in a steady flow field, interpolation is used to turn the discrete white noise into continuous white noise to solve the problem of discontinuity. The “cross” high-pass filtering is used to enhance the textures of streamlines to be more concentrated and continuity strengthened for each streamline. When a sparse noise is used as the input in a steady flow field, we change the directions of background sparse noise according to the directions of vector field to make the streamlines clearer and brighter. In addition, we provide a random initial phase for every streamline to avoid the pulsation effect during animation. The velocities of vector field are encoded in the speed of the same length streamlines so that the running speed of streamlines can express flow rate. Meanwhile, to solve the problem of obvious boundaries when stitching image, we change the streamline tracking constraints. When a white noise is used as an input in an unsteady flow field, double value scattering is used to enhance the contrast of streamlines; moreover, the “cross” high-pass filtering is also adopt instead of two-dimensional high-pass filtering. Finally, we apply the above methods to a case of the surface wave field in typhoon condition. Our experimental results show that applying the methods can generate high-quality wave images and animations. Therefore, it is helpful to understand and study waves in typhoon condition to avoid the potential harm of the waves to people’s lives and property.
Keywordsline integral convolution (LIC) wave data visualization steady and unsteady marine flow field
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We thank Professor LIU Zhanping of the Old Dominion University for providing technical assistance.
- Berger S, Gröller E. 2000. Color-table animation of fast oriented line integral convolution for vector field visualization. In: Proceedings of the 8th International Conference in Central Europe on Computers Graphics. Research Division of Computer Graphics Research Publications, Bohemia, Plzen. p.4–11.Google Scholar
- Höller M, Klose U, Gröschel S, Otto K M, Ehricke H H. 2016. Visualization of MRI diffusion data by a multi-kernel LIC approach with anisotropic glyph samples. In: Linsen L, Hamann B, Hege H C eds. Visualization in Medicine and Life Sciences III. Springer, Cham, Switzerland. p.157–177.CrossRefGoogle Scholar
- Li P K, Zang Y, Wang C, Li J, Cheng M, Luo L, Yu Y. 2016. Road network extraction via deep learning and line integral convolution. In: Proceedings of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, Beijing, China, https://doi.org/10.1109/IGARSS.2016.7729408.Google Scholar
- Weiskopf D. 2009. Iterative twofold line integral convolution for texture-based vector field visualization. In: Möller T, Hamann B, Russell R D eds. Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration. Springer, Heidelberg, Berlin. p.191–211.CrossRefGoogle Scholar