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GPU accelerated marine data visualization method

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Abstract

The study of marine data visualization is of great value. Marine data, due to its large scale, random variation and multi-resolution in nature, are hard to be visualized and analyzed. Nowadays, constructing an ocean model and visualizing model results have become some of the most important research topics of ‘Digital Ocean’. In this paper, a spherical ray casting method is developed to improve the traditional ray-casting algorithm and to make efficient use of GPUs. Aiming at the ocean current data, a 3D view-dependent line integral convolution method is used, in which the spatial frequency is adapted according to the distance from a camera. The study is based on a 3D virtual reality and visualization engine, namely the VV-Ocean. Some interactive operations are also provided to highlight the interesting structures and the characteristics of volumetric data. Finally, the marine data gathered in the East China Sea are displayed and analyzed. The results show that the method meets the requirements of real-time and interactive rendering.

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References

  • Aristizabal, M., Congote, J., Segura, A., Moreno, A., Arregui, H., and Ruiz, O. E., 2012. Hardware-accelerated web visualization of vector fields — case study in oceanic currents. In: Proceedings of GRAPP/IVAPP, 759–763.

    Google Scholar 

  • Asirvatham, A., and Hoppe, H., 2005. Terrain rendering using GPU-based geometry clipmaps. GPU Gems, 2: 27–45.

    Google Scholar 

  • Cabral, B., and Leedom, L. C., 1993. Imaging vector fields using lineIntegral convolution. ACM SIGGRAPH (Special Interest Group on Computer Graphics), 1993, 263–270.

    Google Scholar 

  • Chang, R., Ghoniem, M., Kosara, R., Ribarsky, W., Yang, J., Suma, E., Ziemkiewicz, C., Kern, D., and Sudjianto, A., 2007. WireVis: Visualization of categorical, time-varying data from financial transactions. In: Proceedings of IEEE VAST, 155–162.

    Google Scholar 

  • Chen, G., Li, B., Tian, F. L., Ji, P. B., and Li, W. Q., 2012a. Design and implementation of a 3D ocean virtual reality and visualization engine. Journal of Ocean University of China, 11(4): 481–487.

    Article  Google Scholar 

  • Chen, G., Li, W. Q., Kong, Q. Q., Liu, S. X., Lv, C. J., and Tian, F. L., 2012b. Recent progress of marine geographic information system in China: A review for 2006–2010. Journal of Ocean University of China, 11(1): 18–24.

    Article  Google Scholar 

  • Claes, J., 2004. Real time water rendering. Master thesis. Department of Computer Science, Lund University.

    Google Scholar 

  • Coelho, A., Nascimento, M., Bentes, C., de Castro, M. C. S., and Farias, R., 2004. Parallel volume rendering for ocean visualization in a cluster of PCS. In: Proceeding of VI Brazilian Symposium on Geoinformatics, Campos do Jordão, São Paulo, Brazil, 22–24.

    Google Scholar 

  • Cranley, R., and Patterson, T., 1976. Randomization of number theoretic methods for multiple integration. SIAM Journal on Numerical Analysis, 13: 904–914.

    Article  Google Scholar 

  • Djurcilov, S., Kim, K., Lermusiaux, P. F. J., and Pang, A., 2002. Visualizing scalar volumetric data with uncertainty. Computers and Graphics, 2(26): 239–248.

    Article  Google Scholar 

  • Falk, M., and Weiskopf, D., 2008. Output-sensitive 3D line integral convolution. IEEE Transactions on Visualization and Computer Graphics, 14(4): 820–834.

    Article  Google Scholar 

  • Franke, R., and Nielson, G., 1991. Scattered Data Interpolation and Application: A Tutorial and Survey. Geometric Modeling Computer Graphics — Systems and Applications, Springer Berlin Heidelberg, 131–160.

    Google Scholar 

  • Gonzato, J. C., and Saec, B. L., 2000. On modeling and rendering ocean scenes. Journal of Visualisation and Computer Animation, 11(1): 27–37.

    Article  Google Scholar 

  • Helgeland, A., and Andreassen, O., 2004. Visualization of vector fields using seed LIC and volume rendering. IEEE Transactions on Visualization and Computer Graphics, 10(6): 673–682.

    Article  Google Scholar 

  • Interrante, V., and Grosch, C., 1997. Strategies for effectively visualizing 3D flow with volume LIC. Proceedings of the 8th conference on Visualization, 421–424.

    Google Scholar 

  • Jerry, T., 2001. Simulating ocean water. ACM SIGGRAPH (Special Interest Group on Computer Graphics) 2001 Course Notes, Los Angeles, http://home1.get.net/tssndrf/.

    Google Scholar 

  • Li, G. S., Tricoche, X., and Hansen, C., 2006. GPUFLIC: Interactive and accurate dense visualization of unsteady flows. Proceeding of Eurographics/IEEE-VGTC Symposium on Visualization (Eurovis’ 06), Lisboa, Portugal, 29–34.

    Google Scholar 

  • Nielson, G., Thomas, A., Hamann, F., and Lane, D., 1991. Visualizing and modeling scattered multivariate data. IEEE Computer Graphics and Applications, 11(3): 47–55.

    Article  Google Scholar 

  • Nielson, G., and Tvedt, J., 1994. Comparing Methods of Interpolation Scattered Volumetric Data. State of the art in computer graphics. Springer-Verlag New York, Inc. Secaucus, NJ, USA, 67–86.

    Chapter  Google Scholar 

  • Peng, Z., and Laramee, R. S., 2009. Higher dimensional vector field visualization: A survey. In: Proceedings of TPCG, 149–163.

    Google Scholar 

  • Rezk-Salama, C., Hastreiter, P., Teitzel, C., and Ertl, T., 1999. Interactive exploration of volume line integral convolution based on 3D-texture mapping. Proceedings of the Conference on Visualization, 233–240.

    Google Scholar 

  • Shi, S. X., and Lei, B., 2011. Theory and Practice on China Digital Ocean. Ocean Press, Beijing, 80–100.

    Google Scholar 

  • Weiskopf, D., and Ertl, T., 2004. A hybrid Physical/device-space approach for spatio-temporally coherent interactive texture advection on curved surfaces. Proceedings of Graphics Interface, 263–270.

    Google Scholar 

  • Weiskopf, D., Hopf, M., and Ertl, T., 2001. Hardware-accelerated visualization of Time-varying 2D and 3D vector fields by texture advection via programmable per-pixel operations. Proceedings of the Vision Modeling and Visualization Conference, 439–446.

    Google Scholar 

  • Weiskopf, D., Schafhitzel, T., and Ertl, T., 2007. Texture-based visualization of unsteady 3D flow by real-time advection and volumetric illumination. IEEE Transactions on Visualization and Computer Graphics, 13(3): 569–582.

    Article  Google Scholar 

  • Zhang, F., Li, H. Q., Liu, J., and Li, S. H., 2011. Research and realization of visual digital ocean system. Marine Science Bulletin, 13(1): 87–96.

    Google Scholar 

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Correspondence to Ge Chen.

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Li, B., Chen, G., Tian, F. et al. GPU accelerated marine data visualization method. J. Ocean Univ. China 13, 964–970 (2014). https://doi.org/10.1007/s11802-014-2304-3

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  • DOI: https://doi.org/10.1007/s11802-014-2304-3

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