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Visualizing Uncertainty in Volume Rendering

Visualizing Uncertainty in Volume Rendering. Suzana Djurcilov * , Kwansik Kim * , Pierre Lermusiaux † and Alex Pang *. * UC Santa Cruz † Harvard University. OVERVIEW. Introduction Inline Approach Post-Processing Approach Future Directions. Uncertainty in Volume Rendering.

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Visualizing Uncertainty in Volume Rendering

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  1. Visualizing Uncertainty in Volume Rendering Suzana Djurcilov*, Kwansik Kim*, Pierre Lermusiaux† and Alex Pang* * UC Santa Cruz † Harvard University

  2. OVERVIEW Introduction Inline Approach Post-Processing Approach Future Directions

  3. Uncertainty in Volume Rendering • Volume Rendering is a single value method • Need to add a second parameter without diminishing the output of the volume rendered image • Want a task-specific visualization

  4. Application Domain • Ocean Model (Mid-atlantic) from Harvard • Focus: temperature and salinity along the shelf-break • Uncertainty is the standard deviation over several time steps

  5. Inline Approach • Direct Volume Rendering (DVR) • 1D Transfer Function • Opacity mapping of uncertainties • 2D Transfer function

  6. Inline Approach Direct Volume Rendering (DVR) Example visualization of Salinity data using DVR : opacity C: color intensity E: emission

  7. 1D Transfer function • Thresholding • Map uncertainty to opacity • Leave color transfer intact • High uncertainty areas more noticeable

  8. 1D Transfer Function : uncertainty thresholding DVR of uncertainty > 0.2 DVR of uncertainty > 0.5

  9. 1D Transfer Function : mapping uncertainties to opacity values Transfer function Increasing opacity with uncertainty salinity temperature

  10. 1D Transfer Function : higher contrast Transfer function Increasing opacity with uncertainty temperature salinity

  11. 2D Transfer function - Histogram • Create a graph of data vs. uncertainty • Map different regions to different colors • Override the transfer function

  12. 2D Transfer Function : histogram

  13. 2D Transfer Functions 2D transfer function Salinity data

  14. 2D Transfer Functions 2D transfer function Salinity data

  15. Post-processing approach • Get a separate volume rendering of the primary data value and of uncertainty • Combine the two renderings into a single image • Primary value still discernible

  16. +

  17. Color background is preserved • Multi-variable representation specific to uncertainty • Holes can be larger if needed • Hole color can not be part of the transfer function

  18. Variable hole size 1 pixel 4 pixels

  19. Speckle intensity • Higher uncertainty --> darker hole • Gray-scale color • Vary both density and shade of hole

  20. Using Texture • Rough textures naturally convey uncertainty • Random elements introduced into the image • Textures can be from nature (sandstone, gravel) or procedurally created • Higher contrast -> higher uncertainty

  21. 2D textures • Create textures for 5 different uncertainty levels • Quantize uncertainty and map to different texture levels • Blend the texture with the original DVR • Shade the original pixel color according to the matching texture

  22. Texture Examples

  23. Adding Noise • Change the DVR image directly • Alter pixels in areas of high uncertainty • Distance in color space proportional to uncertainty

  24. Noise Example

  25. Future Work • Extend the application domain • Incorporate depth information into post-processing • Non-scalar (range, distribution) uncertainty

  26. Acknowledgements • ONR N00014-00-1-0764 and N00014-00-1-0771 • NASA NCC2-5281 • DOE W-7405-ENG-48 • NSF ACI-9908881 • DARPA grant N66001-97-8900

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