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Fast LIC Image Generation Based on Significance Map

  • Li Chen
  • Issei Fujishiro
  • Qunsheng Peng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1940)

Abstract

Although texture-based methods provide a very promising way to visualize 3D vector fields, they are very time-consuming. In this paper, we introduce the notion of “significance map”, and describe how significance values are derived from the intrinsic properties of a vector field. Based on the significance map, we propose techniques to accelerate the generation of a line integral convolution (LIC) texture image, to highlight important structures in a vector field, and to generate an LIC texture image with different granularities. Also, we describe how to implement our method in a parallel environment. Experimental results illustrate the feasibility of our method.

Keywords

Vector Field Texture Image Curvilinear Grid IEEE Visualization Texture Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Cabral, B., Leedom, C.: Image Vector Field Using Line Integral Convolution. In: Computer Graphics Proceedings, Annual Conference Series. ACM SIGGRAPH, New York (1993) 263–272Google Scholar
  2. [2]
    Stalling, D., Hege, H.: Fast and Resolution Independent Line Integral Convolution. In: Computer Graphics Proceedings, Annual Conference Series. ACM SIGGRAPH, New York (1995) 249–256Google Scholar
  3. [3]
    Forssell, L. K., Cohen, S. D.: Using Line Integral Convolution for Flow Visualization: Curvilinear Grids, Variable-speed Animation and Unsteady Flows. IEEE Transactions on Visualization and Computer Graphics, Vol.1, No.2 (1995) 133–141CrossRefGoogle Scholar
  4. [4]
    Mao, X., et al.: Line Integral Convolution for Arbitrary 3D Surfaces Through Solid Texturing. In: Lefer, W., Grave, M. (eds.): Visualization in Scientific Computing’ 97. Springer-Verlag, Wien (1997) 57–69Google Scholar
  5. [5]
    Shen, H.-W., Johnson, C., Ma, K.-L.: Visualizing Vector Fields Using Line Integral Convolution and Dye Advection. In: Proceedings of 1996 Symposium on Volume Visualization. ACM SIGGRAPH, New York (1996) 63–70Google Scholar
  6. [6]
    Shen, H.-W., Kao, D.: UFLIC: Line Integral Convolution Algorithm for Visualizing Unsteady Flows. In: Proceedings of IEEE Visualization’ 97. ACM Press, New York (1997) 317–322Google Scholar
  7. [7]
    Okada, A., Kao, D.: Enhanced Line Integral Convolution with Flow Feature Detection. In: SPIE, Vol. 3017, Visual Data Exploration and Analysis IV (1997) 206–217Google Scholar
  8. [8]
    Liu, M.-H., Banks, D. C.: Multi-Frequency Noise for LIC. In Proceedings of IEEE Visualization’ 96. ACM Press, New York (1996) 121–126Google Scholar
  9. [9]
    Wegenkittl, R., Groller, E., Purgathofer, W.: Animating Flow Fields: Rendering of Oriented Line Integral Convolution. In: Proceedings of Computer Animation’97. IEEE Computer Society Press, Los Alamitos (1997) 15–21Google Scholar
  10. [10]
    Verma, V., Kao, D., Pang, A.: PLIC: Bridging the Gap Between Streamlines and LIC. In: Proceedings of IEEE Visualization’99.ACM Press, New York (1999) 341–348Google Scholar
  11. [11]
    Chong, M. S., Perry, A. E., Cantwell, B. J.: A General Classification of 3D Flow Fields. Physics of Fluids Ann., Vol. 2, No.5 (1990) 765–777CrossRefMathSciNetGoogle Scholar
  12. [12]
    Helman, J., Hesselink, L.: Visualizing Vector Field Topology in Fluid Flows.IEEE Computer Graphics and Applications, Vol.11, No.3 (1993) 36–46CrossRefGoogle Scholar
  13. [13]
    Sujudi, D., Haimes, R.: Identification of Swirling Flow in 3-D Vector Fields. AIAA-95-1715 (1995)Google Scholar
  14. [14]
    Kenwright, D.: Automatic Vortex Core Detection. IEEE Computer Graphics and Applications, Vol. 18, No. 4 (1998) 70–74CrossRefGoogle Scholar
  15. [15]
    Roth, M., Peikert, R.: A Higher-Order Method for Finding Vortex Core Lines. In: Proceedings of IEEE Visualization’ 98. ACM Press, New York (1998) 143–150Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Li Chen
    • 1
    • 3
  • Issei Fujishiro
    • 2
    • 1
  • Qunsheng Peng
    • 3
  1. 1.Research Organization for Information Science & TechnologyMinato-ku, TokyoJapan
  2. 2.Department of Information Sciences, Faculty of ScienceOchanomizu UniversityBunkyo-ku, TokyoJapan
  3. 3.State Key Lab. of CAD&CGZhejiang UniversityHangzhouP. R. China

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