1. High-Quality Volume Graphics on Consumer PC Hardware
Klaus
Engel
Joe
Kniss
Markus
Hadwiger
Christof
Rezk-Salama

2. a f RGB Map data value f to color and opacity Shading, Compositing…
Human Tooth CT
a(f)
RGB(f) f
Shading,
Compositing…

3. Optical Properties
Color (RGB)
Emissive term ~ =

4. Optical Properties ~ Alpha (a.k.a. opacity or extinction) = =
Attenuates light based on density ~ = =

5. Optical Properties ~ Traditional Volume Rendering Equation
Emission & absorption ~

6. Optical Properties
Scale alpha values based on sample rate (sr)
1.3 .7

7. Transfer Function Transform scalar data value into optical properties
Use optical properties to solve integral
Very easy to implement
Data is a texture
Transfer function is a lookup
Compute Riemann sum using “over operator”

8. Transfer Function Pre-classification Post-classification
Transfer function evaluated before interpolation, i.e. interpolation of colors not data
Transfer function evaluated after interpolation, i.e. data is interpolated first

9. Implementation Two choices: Texture Lookup Table
glColorTable*
Varies depending on hardware, may require a special texture data format
Fast
Dependent Texture Read
Very hardware dependent
Becoming more general, see OpenGl 2.0
Slower but more flexible…

10. Transfer Function Problem: f(x,y,z) No shape or depth queues
No shading.
color
alpha
f(x,y,z)

11. Transfer Function Solution: Faux Shading f(x,y,z)
Ramp color to black with alpha
Silhouette edges
color
alpha
f(x,y,z)

12. Transfer Function Better: Surface Shading Slower, requires normal
More flexible

13. Transfer Function Better: Surface Shading Slower, requires normal
More flexible
Faux shading enhances

14. Transfer Function Problem: Can’t surface shade homogeneous regions
Need good gradients
Sensitive to noise

15. Transfer Function Solution: Surface scalar (s)
Only shade high gradient magnitudes:
Or, add s to TF
Interpolate…

16. Transfer Function Problem: How did the light get there?
No attenuation through volume
Not realistic!

17. Transfer Function Solution: Shadows Better depth queues
Dramatic effects

18. Shadows
Image plane r1 r0
Eye
Light

19. Shadows
Sample ri (s)
Image plane r1 r0 IL l0
Eye ~

20. Shadows Implementation: 2 passes
Attenuate from the light source
Render from the eye
Store light attenuation in second volume
Multiply color by attenuation from shadow volume

21. Shadows Disadvantages: Difficult to build shadow volume on the card
Slow to build off the card
Additional volume required
Attenuation leakage
Blurry shadow boundaries
Low resolution shadows!

22. Shadows Alternative: Incremental shadows
Generate shadows one slice at a time
Only use a 2D buffer
Image space shadow computation
All on card
Half angle slicing

23. Slicing from light’s point of view
Shadows
Eye
Slicing from light’s point of view

24. Slicing from eye’s point of view
Shadows
Eye
Slicing from eye’s point of view

25. Half angle slicing: good from either point of view
Incremental Shadows
Eye
Half angle slicing: good from either point of view

26. Similar aspect ratio from both points of view
Incremental Shadows
Similar aspect ratio from both points of view

27. Incremental Shadows *
Slice pass 1

28. Incremental Shadows
Slice pass 2

29. Incremental Shadows Advantages: Disadvantages: Screen space shadows
No leakage
Use render to texture to optimize
Shades perturbed volumes
Simple implementation
Disadvantages:
Aliasing at sharp opacity changes
Fix with slightly larger light buffer

30. Shadows Problem: Shadows still too dark
Direct attenuation is inadequate
Need to handle higher order light transport effects
Shadows

31. Shadows Solution: Translucency One consequence of light scattering
Smoke, clouds, skin, wax….
Shadows
Translucent

32. Translucency
Wax:
Real
Shadows

33. Translucency
Wax:
Real
Shadows
Translucent

34. Translucency Add indirect attenuation
Direct attenuation, same as shadows
Blurred indirect attenuation, includes an indirect alpha

35. Direct (Id) and indirect (Ii) attenuation
Translucency
Direct (Id) and indirect (Ii) attenuation

36. Translucency How? Same as shadows (two light buffers)
Sample previous light buffer multiple times for blur
Ping-pong blending
Store indirect in a color component
Sum direct and indirect in fragment shader for the eye pass
Only use direct attn. for eye pass

37. Translucency Problem: Still doesn’t look right Real Shadows
Translucent

38. Translucency Solution: add spectral attenuation Real
Translucent w/spectral attn.

39. Translucency Spectral attenuation:
Attenuate some colors more than others
Spectral indirect attn. is simplest
Need separate alpha for RGB
Store in RGB components of light buffer

40. Translucency Indirect alpha vs. transport color Alpha: Transport:
Transport color is
easier to specify

41. Optical Properties Recap: Reflective color/Emission (RGB)
Direct attenuation/alpha (A)
Surface scalar (s)
Indirect attenuation (Ar,Ag,Ab)
Others?
Scattering, absorption, phase function, density, emission, index of refraction…

42. Transfer function
Specification
Simple, easy
Expressive
Guided

43. Transfer function Typical: 1D linear ramps f(x,y,z)
Independent R,G,B,A control
Difficult
Trial and error
alpha
f(x,y,z)

44. Transfer function Problem: f(x,y,z) RGB = bad color space for humans
No concept of features
alpha
f(x,y,z)

45. Transfer function Better: set color at control points f(x,y,z)
Use HSV or HLS color spaces
Simplified interface
Still no guidance
alpha
f(x,y,z)

46. Transfer function Guided techniques: Design Galleries Thumbnails
Semi-Automatic
Dual-domain interaction

47. Design Galleries
Treat TF and rendering as a high dimensional parameter space
Stochastically sample space
Cluster images based on fitness
Select best looking image

48. Design Galleries

49. Design Galleries Computationally expensive Difficult to implement
Not guided by dataset specifics
Only handles 1D transfer functions

50. Thumbnails Visual history of changes Show important regions of TF
Show effects of potential changes

51. Thumbnails
spreadsheets

52. Thumbnails
Parameterization

53. Semi-automatic Volumetric edge detection
Use first and second derivatives
Build histogram volumes
Use simplified interface
Generate 1D or 2D TFs

54. Semi-automatic
Position of boundary center

55. Semi-automatic

56. Semi-automatic Identifies data ranges of boundaries
Still requires hand-editing
Not really an interactive process
Demonstrates the value of histograms

57. Transfer function What is a 2D transfer function
Multiple values per sample point
2D lookup table
Each value is an axis of TF
Better specificity
More complicated to use

58. Transfer function
RGB( )
Generalize…
( )

59. Transfer function
( , )
RGB( , )
Modify…

60. Transfer function
( , )
RGB( , )
Modify…

61. - + Transfer function RGB ( , , ) Second directional derivative
measured with
Hessian -

62. Transfer function +
RGB ( , , )
Done -

63. Transfer function Multi-dimensional TFs
Data value, gradient magnitude, second derivative
Multivariate, i.e. multiple values
Implement as dependent texture read, 1D, 2D, 3D texture for TF

64. Transfer function Multiple scans Color data Multiple variables
MRI-T1,T2,PD
Cryosection
Simulation

65. Transfer function
Problem: How do we interact with a higher dimensional TF?
Larger parameter space
Unintuitive feature identification
Greater demands on user interface

66. Transfer function Solution: It is a process!! Data set guidance
Improved classification
Intuitive feature identification

67. 1
“Default” transfer function
Initial

68. 1
Probing
Initial 2
Explore

69. 1 Initial 2 Explore 3 Specify Transfer function widget Manual
Dual-domain interaction
Initial 2
Explore 3
Specify

70. 1 Initial 2 Explore 4 Refine 3 Specify
Use widgets to tune the transfer function
Initial 2
Explore 4
Refine 3
Specify

71. Interactive 1 Initial 2 Explore 4 Refine 3 Specify
Understanding from immediate feedback
Initial 2
Explore 4
Refine 3
Specify
Interactive

72. Classification Discrete features Basic functions
Direct manipulation widgets
V3 slider(s) V2 V1

73. Guidance
Histograms
Blue
Red
Green

74. Guidance
Probing
Identify features
in transfer function
Chapel Hill CT

75. Guidance
Dual-domain interaction
Classify features by pointing at them

76. Refinement
Manipulate well defined control points

77. Transfer function
Advantages:
Better feature discrimination

78. Technique
Animated transfer function