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Footprint Evaluation for Volume Rendering

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If we place D at the origin, the footprint function is. This footprint function defines how much voxel(D) will deposit its value to ... – PowerPoint PPT presentation

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Title: Footprint Evaluation for Volume Rendering


1
Footprint Evaluation for Volume Rendering
  • Presentation by
  • Lian Jiang
  • Gaozhu Peng
  • Sandeep Gupta

2
  • INTRODUCTION
  • Forward Mapping
  • Easy to Parallel
  • ENHANCEMENTS
  • Supports Perspective without excessive cost
  • Adaptive Re-sampling

3
  • Problem
  • How to fill the pixel values between
    the volume project sample?

4
Rendering Pipeline
  • Transformation
  • Shading
  • Reconstruction
  • Visibility

5
  • Transformation
  • 1. Original unit sphere (U)
  • 2. Grid scale transformation ( Matrix S)
  • Viewing transformation (V)
  • Shading
  • Pre-shaded pipeline

6
Footprint definition
voxel
3D extent
7
If we place D at the origin, the footprint
function is
This footprint function defines how much voxel(D)
will deposit its value to pixel(Dxx, Dyy)
?(Dx, Dy, Dz)footprint(x,y)
8
Example Sphere Kernel
Approximate the 3D kernel h(x,y,z) extent by a
sphere
9
Why we need Footprint Table?
Answer
  • Evaluating footprint(x,y) on the fly is too time
    Consuming involves integration of the kernel
    function h(x,y,z)
  • We can build the footprint table at
    preprocessing time
  • The kernel function can be any cone, Gaussian
    and sphere (depends on the renderer)

10
How to use Footprint Table?
Answer Footprint value lookup
  • For rectilinear meshes, the footprint of each
    sample is
  • identical except for an image-space
    offset.
  • The renderer only needs to calculate
    footprint function
  • once for each orthographical view.
  • Weight is calculated by table lookup at the
    footprint
  • function value at each pixel that lies
    within the
  • footprints extent

11
Effect of number of entries of the table
  • Time versus space tradeoff
  • If a lot entries, nearest neighbor works fine
  • If coarse, interpolate from the nearest
  • samples.
  • For smaller table size, interpolation gives
  • much better results.
  • Produce intuitive images

12
How to deal with Visibility
Answer
  • Splatting uses the compositing operator to
    perform
  • visibility
  • Either front to back or back to front
    compositing
  • The problem for simply composite samples
    footprint
  • onto the accumulation buffer sample by sample

13
  • ENHANCEMENTS
  • Supports Perspective without excessive cost
  • Adaptive Re-sampling

14
Volume Rendering of a high potential iron
protein (rendered by VTK)
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