We describe two techniques for rendering isosurfaces in multiresolution volume data such that the uncertainty (error) in the data is shown in the resulting visualization. In general the visualization of uncertainty in data is difficult, but the nature of isosurface rendering makes it amenable to an effective solution. In addition to showing the error in the data used to generate the isosurface, we also show the value of an additional data variate on the isosurface. The results combine multiresolution and uncertainty visualization techniques into a hybrid approach. Our technique is applied to multiresolution examples from the medical domain.
In this paper, uncertainty visualization is added to isosurface rendering by mapping uncertainty values to one of three color parameters (hue, brightness, or saturation), or using texture. Mapping to a color parameter allows the user to choose the range of a single parameter, keeping the other two fixed. Because changes in hue are most visually noticeable, it is the recommend parameter to use since brightness is needed to decipher the shape of the isosurface. Texture can also be added to the rendering to show areas of uncertainty by adding texture and varying the opacity of the texture with uncertainty. The benefit of using texture is that the color mapping can be used for the display of another variate, since the texture interferes only slightly with the color parameters. Isosurface rendering is an ideal technique to apply uncertainty visualization since the visualized data has the same value, and thus this value does not need to be visualized, leaving a lot of options to visualize uncertainty.
Isosurface rendering, color mapping, texture mapping, multi resolution data, opacity mapping
Color mapping, texture with opacity mapping
@InProceedings{ rhodes:2003:UVIR,
author = "Philip J. Rhodes and Robert S. Laramee and R. Daniel
Bergeron and Ted M. Sparr",
title = "Uncertainty Visualization Methods in Isosurface
Rendering",
booktitle = "EUROGRAPHICS 2003 Short Papers",
pages = "83-88",
year = "2003",
}
I. Boada, I. Navazo, and R. Scopigno. Multiresolution Volume Visualization with a Texture-Based Octree. In The Visual Computer, volume 17(3), pages 185-197. Springer, 2001.
A. Cedilnik and P. Rheingans. Procedural annotation of uncertain information. In Proceedings Visualization 2000, pages 77-84. IEEE Computer Society Technical Committee on Computer Graphics, 2000.
P. Cignoni, C. Rocchini, and R. Scopigno. Metro: Mea- suring Error on Simplified Surfaces. Computer Graph- ics Forum, 17(2):167-174, 1998.
W. Hibbard. Connecting People to Computations and People to People. Computer Graphics, 32(3):10-12, 1998.
W. Hibbard and D. Santek. Interactivity is the Key. In Proceedings of the Chapel Hill Workshop on Volume Visualization, pages 39-43, May 1989.
G. J. Hunter and M. F. Goodchild. Managing Uncer- tainty in Spatial Databases: Putting Theory into Prac- tice. In URISA Proceedings, volume 1, pages 1-14,
E. C. LaMar, B. Hamann, and K. I. Joy. Multiresolution Techniques for Interactive Texture-based Volume Visu- alization. In David Ebert, Markus Gross, and Bernd Hamann, editors, IEEE Visualization '99, pages 355- 362, San Francisco, 1999. IEEE.
R. S. Laramee and R. D. Bergeron. An Isosurface Continuity Algorithm for Super Adaptive Resolution Data. In John Vince and Rae Earnshaw, editors, Ad- vances in Modelling, Animation, and Rendering: Com- puter Graphics International (CGI 2002), pages 215- 237, Bradford, UK, July 1-5 2002. Computer Graphics Society, Springer.
S. K. Lodha, A. Pang, R. E. Sheehan, and C. M. Wit- tenbrink. UFLOW: Visualizing Uncertainty in Fluid Flow. In IEEE Proceedings of the Conference on Visu- alization, pages 249-254, Los Alamitos, October 27- November 1 1996.
S. K. Lodha, C. M. Wilson, and R. E. Sheehan. LIS- TEN: Sounding Uncertainty Visualization. In Roni Yagel and Gregory M. Nielson, editors, IEEE Visual- ization '96, pages 189-196. IEEE, 1996.
W. E. Lorensen and H. E. Cline. Marching Cubes: a High Resolution 3D Surface Construction Algorithm. In SIGGRAPH '87 Conference Proceedings (Anaheim, CA, July 27-31, 1987), pages 163-170. Computer Graphics, Volume 21, Number 4, July 1987.
A. Pang and J. Furman. Data Quality Issues in Visu- alization. In SPIE proceedings on Visual Data Explo- ration and Analysis, volume 2178, pages 12-23, 1994.
P. J. Rhodes, R. D. Bergeron, and T. M. Sparr. A Data Model for Distributed Multiresolution Multisource Sci- entific Data. In G. Farin, H. Hagen, and B. Hamann, editors, Hierarchical and Geometrical Methods in Sci- entific Visualization, Heidelberg, Germany, 2002.
Q. Shen, A. Pang, and S. Uselton. Data Level Com- parison of Wind Tunnel and Computational Fluid Data Dynamics Data. In Proceedings of the IEEE Confer- ence on Visualization, pages 415-418, 1998.
C. M. Wittenbrink, A. T. Pang, and S. K. Lodha. Glyphs for Visualizing Uncertainty in Vector Fields. IEEE Transactions on Visualization and Computer Graphics, 2(3):266-279, September 1996.
P. C. Wong and R. D. Bergeron. Authenticity Anal- ysis of Wavelet Approximations in Visualization. In Proceedings of the IEEE Conference on Visualization. IEEE, 1995.
P. C. Wong and R. D. Bergeron. Performance Evalua- tion of Multiresolution Isosurface Rendering. In Pro- ceedings, Dagstuhl '97 Scientific Visualization, pages 332-341. IEEE Computer Society Press, 2000.