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Volume Rendering Data with Uncertainty Information

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Book cover Data Visualization 2001

Part of the book series: Eurographics ((EUROGRAPH))

Abstract

This paper explores two general methods for incorporating volumetric uncertainty information in direct volume rendering. The goal is to produce volume rendered images that depict regions of high (or low) uncertainty in the data. The first method involves incorporating the uncertainty information directly into the volume rendering equation. The second method involves post-processing information of volume rendered images to composite uncertainty information. We present some initial findings on what mappings provide qualitatively satisfactory results and what mappings do not. Results are considered satisfactory if the user can identify regions of high or low uncertainty in the rendered image. We also discuss the advantages and disadvantages of both approaches.

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References

  1. Andrej Cedilnik and Penny Rheingans. Procedural annotation of uncertain information. In Proceedings of Visualization 00, pages 77–84. IEEE Computer Society Press, 2000.

    Google Scholar 

  2. Suzana Djurcilov and Alex Pang. Visualizing sparse gridded datasets. IEEE Computer Graphics and Applications, 20(5):52–57, September 2000.

    Article  Google Scholar 

  3. Victoria Interrante. Harnessing natural textures for multivariate visualization. IEEE Computer Graphics and Applications, 20(6):6–11, November/December 2000.

    Article  Google Scholar 

  4. G. Kindlmann and J.W. Durkin. Semi-automatic generation of transfer functions for direct volume rendering. In IEEE Symposium on Volume Visualization, pages 79–86, 170. IEEE, 1998.

    Google Scholar 

  5. P.F.J. Lermusiaux. Data assimilation via error subspace statistical estimation, Part ii: Middle Atlantic Bight shelfbreak front simulations and ESSE validation. Monthly Weather Review, 127(7):1408–1432, 1999.

    Article  Google Scholar 

  6. E. Levy, G. Gawarkiewicz, and F. Bahr. The ONR shelfbreak PRIMER experiment: shelfbreak frontal dynamics in the Middle Atlantic Bight. URL: http://matisse.whoi.edu/primerxd, 1999.

  7. A. Pang, C.M. Wittenbrink, and S. K. Lodha. Approaches to uncertainty visualization. The Visual Computer, 13(8):370–390, 1997.

    Article  Google Scholar 

  8. A.R. Robinson. Physical processes, field estimation and an approach to interdisciplinary ocean modeling. Earth-Science Review, 40:3–54, 1996.

    Article  Google Scholar 

  9. A. Tarantola. Inverse Problem Theory. Methods for Data Fitting and Model Parameter Estimation. Elsevier Science Publishers, 1987.

    Google Scholar 

  10. Craig M. Wittenbrink. IFS fractal interpolation for 2D and 3D visualization. In IEEE Visualization’ 95, pages 77–84, Atlanta, GA, November 1995. IEEE.

    Google Scholar 

  11. Craig M. Wittenbrink, Alex T. Pang, and Suresh K. Lodha. Glyphs for visualizing uncertainty in vector fields. IEEE Transactions on Visualization and Computer Graphics, 2(3):266–279, September 1996. Short version in SPIE Proceeding on Visual Data Exploration and Analysis, pages 87-100, 1995.

    Article  Google Scholar 

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© 2001 Springer-Verlag Wien

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Djurcilov, S., Kim, K., Lermusiaux, P.F.J., Pang, A. (2001). Volume Rendering Data with Uncertainty Information. In: Ebert, D.S., Favre, J.M., Peikert, R. (eds) Data Visualization 2001. Eurographics. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6215-6_26

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  • DOI: https://doi.org/10.1007/978-3-7091-6215-6_26

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83674-3

  • Online ISBN: 978-3-7091-6215-6

  • eBook Packages: Springer Book Archive

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