1. Volume Visualization Chap. 10 November 20 , 2008 Jie Zhang Copyright ©
CDS 301
Fall, 2008
Jie Zhang
Copyright ©

2. Volume Visualization Visualize a 3D Scalar Dataset
What? Why is difficult? How?
Visualize a 3D Scalar Dataset

3. Outline 10.1. Motivation 10.2. Volume Visualization Basics
Classification
Maximum Intensity Projection
Average Intensity Function
Isosurface Function
Compositing Function
Volume Shading
10.3. Image Order Technique
10.4. Object Order Technique
10.5. Volume Rendering versus Geometric Rendering 3

4. Methods We Knew
A floating-point value is encoded in 32 bits
Slicing 4

5. Methods We Knew Generalized Slicing: Multiple transparent slices
A floating-point value is encoded in 32 bits
Generalized
Slicing:
Multiple transparent slices 5

6. Methods We Knew Isosurface
A floating-point value is encoded in 32 bits
Isosurface 6

7. Methods We Knew Generalized Isosurfaces
A floating-point value is encoded in 32 bits 7

8. Principle of Volume Visual.
The Ray
A floating-point value is encoded in 32 bits 8

9. Principle of Volume Visual.
Create a two dimensional image that reflects, at every pixel, the data along a ray parallel to the viewing direction
Ray function: synthesize the points along the ray
Transfer function: map the value of a data point on the ray to a color and opacity (RGBA) value; also called classification
A floating-point value is encoded in 32 bits 9

10. Maximum Intensity Projection Function (MIP)
The ray function first computes the maximum scale value along the ray, and then maps this value to the color of pixel P
A floating-point value is encoded in 32 bits 10

11. Maximum Intensity Projection Function (MIP)
A floating-point value is encoded in 32 bits 11

12. Average Intensity Function
The ray function is the average intensity
A floating-point value is encoded in 32 bits 12

13. Isosurface Function Detecting pixels with the value σ along the ray
A floating-point value is encoded in 32 bits 13

14. Isosurface Function A 3-D binary image with shading
A floating-point value is encoded in 32 bits 14

15. Compositing Function A general ray function
The color C(p) of a given pixel p is a superposition of the contributions of the color c(t) of all voxels q(t) along the ray r(p)
A floating-point value is encoded in 32 bits 15

16. Compositing Function
Volumetric Illumination Model: color c(t) emitted at location q(t) is attenuated by the opacity of points situated between q(t) and the view plan 16

17. Compositing Function
Volumetric Illumination Model 17

18. Compositing Function
Yield high quality of volume rendering 18

19. Compositing Function Specify the transfer function for colors;
Skin: dark brown
Soft bone: light yellow
Hard bone: bright white
Hard bone
Specify the transfer function for colors;
Specify the transfer function for opacity 19

20. Compositing Function
Skin: dark brown
Soft bone: light yellow
Hard bone: bright white
Hard bone
Volume data without sharp boundary: smooth transfer functions 20

21. Volumetric Shading
Apply the Phong lighting model to the data value at each voxel
The normal is calculated based on the isosurface of the data value at the voxel
Phong Lighting Model
A floating-point value is encoded in 32 bits 21

22. Phong Lighting Model Three components:
I(p,v,L): intensity of the scene point
Il: Intensity of the light
p: location of the scene point
V: direction vector from p to the viewpoint
L: direction vector from the light to p
n: surface normal at p
r: direction of the reflecting light
α: specular power α
Three components:
Camb: ambient light, effect of other objects, assuming to be constant
Cdiff: diffuse light, scattering of the surface, equal in all direction
Cspec: specular light, mirror-like reflection

23. Volumetric Shading No Lighting Diffuse Lighting Specular Lighting
A floating-point value is encoded in 32 bits
No Lighting
Diffuse Lighting
Specular Lighting 23

24. (continued) Volume Visualization
Chap. 10
Nov. 25, 2008 24

25. Volumetric Rendering Versus Geometric Rendering
Method: using compositing function
Advantage: all data points are considered
Disadvantage: computationally costly
Geometric rendering
Method: cutting, selection
Advantage: computationally fast
Disadvantage: Sparse representation of the data
A floating-point value is encoded in 32 bits 25

26. End of Chap. 10
Note: All sections are covered except 10.3 and 10.4 26