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Visualizing scalar volumetric data with uncertainty

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

Increasingly, more importance is placed on the uncertainty information of data being displayed. This paper focuses on techniques for visualizing 3D scalar data sets with corresponding uncertainty information at each point which is also representedas a scalar value. In Djurcilov (in: D. Ebert, J.M. Favre, R. Peikert (Eds.), Data Visualization 2001, Springer, Berlin, 2001), we presentedtwo general methods (inline DVR approach anda post-processing approach) for carrying out this task. The first methodinvolves 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.

Volume rendering data with uncertainty information

Djurcilov, S., K. Kim, P.F.J. Lermusiaux and A. Pang, 2001. Volume rendering data with uncertainty information. In "Data visualization", Joint Eurographics - IEEE TCVG Symposium on Visualization, D. Ebert, J. M. Favre and R. Peikert (Eds.), Springer-Verlag. pp. 243-252, 355-356.

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.