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Volume Rendering Architecture Case Study - VolumePro

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Pre-computed reflectance maps for diffuse and specular illumination ... Specular reflection. Ambient reflection. Emission. Ray Casting Accumulating Color ... – PowerPoint PPT presentation

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Title: Volume Rendering Architecture Case Study - VolumePro


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Volume Rendering ArchitectureCase Study -
VolumePro
  • Presentation By
  • Boaz Ophir
  • Isak Levinson

Visualization and Animation winter 2002
3
Volume Visualization Applications
  • Applications
  • Medical data
  • Seismic data
  • Finite element models
  • Demands
  • Real time
  • Interactivity
  • Low cost

4
Challenges
  • Huge amounts of voxel data
  • Data access
  • Storage
  • Transport
  • Computation
  • Relatively simple computations per voxel

5
Solution Ideas
  • Data Acces
  • Smart data partitioning
  • Parallel data access
  • Computation
  • Parallelizm
  • Pipelining

6
VolumePro General Overview
  • Single chip real time volume rendering system for
    PCs
  • System consists of
  • PCI card
  • Companion 3-D graphics card
  • Software
  • VolumePro PCI card
  • 128MB volume memory
  • Vg500 rendering chip (ASIC)

7
VolumePro General Overview (cntd.)
  • Chip architecture based on the cube-4 volume
    rendering architecture
  • SUNY stony brook
  • EM-cube
  • Enhanced memory cube-4
  • Produced by Mitsubishi electric real time
    visualization group

8
Main Features
  • Data
  • Rectilinear datasets
  • 8/12bit voxels
  • Per-sample
  • Classification
  • Interpolation
  • Gradient estimation
  • Phong ilumination
  • Compositing
  • All parameters can be adjusted in RT

9
Main Features (cntd.)
  • Classification
  • Assigns RGBA values using 4096x36 LUT
  • 24 bit precision RGB values
  • 12 bit precision a values
  • Interpolation
  • Tri-linear weighted average of closest voxels
  • Phong Ilumination
  • Pre-computed reflectance maps for diffuse and
    specular illumination
  • Each map sums all illumination from all light
    sources
  • Unlimited number of directional light sources
  • Opacity and illumination are optionally
    multiplied with gradient magnitude
  • Base plane Compositing
  • Front-to-back alpha blending
  • Minimum/maximum intensity projections

10
System Architecture
  • 4 identical rendering pipelines
  • 125 MHz
  • On-chip voxel distribution network
  • Voxel memory
  • Pixel memory
  • PCI bus
  • Block-and-bank skewing scheme

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System Architecture (cntd.)
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Rendering Algorithm
  • Create 2D image from the volume data set

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Ray Casting
  • Casting the rays through the volume and define
    sample points
  • Assigning color and opacity to the sample points
  • Interpolating voxels to the new sample points
  • Calculate gradients
  • Assign lighting to the image
  • Accumulate color and opacity to create the image

14
Ray Casting Casting Rays
  • Casting the rays through the volume and define
    sample points

15
Ray Casting Casting Rays 2
  • Shear-warp matrix
  • Handle unisotropic data
  • Advantage voxels processed in planes slices

16
Ray Casting Assigning Color
  • Assign RGBA value to each interpolated voxel
  • RGBA is taken from 4 lookup tables

17
Ray Casting Interpolation
Trilinear interpolation of voxels to the new
sample points
18
Ray Casting Gradients
  • Method
  • Central differences
  • User pre-computed
  • Purpose
  • Correct unisotropic images
  • Used by the illumination model
  • Used for color accumulation

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Ray Casting Illumination
  • Phong lighting model
  • Calculate gradients
  • Diffuse reflection
  • Specular reflection
  • Ambient reflection
  • Emission

20
Ray Casting Accumulating Color
  • Accumulate color and opacity to create the image
  • Perform alpha correction
  • Front to back accumulation

21
Ray Casting Accumulating Color Example
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Voxel Memory
  • Four 16-bit memory interfaces
  • Up to 128 MB SDRAM
  • Miniblocks
  • 2x2x2 neighbouring voxels
  • Miniblocks are stored linearly
  • Read/written in bursts (SDRAM fast burst mode)
  • 3-D skewing of miniblocks
  • Distribution across memory modules
  • Groups of 4 adjacent MBs (in any direction) are
    stored in separate memory modules

23
Voxel Memory (cntd.)
  • Further skewing whithin each memory module so
    adjacent MBs never fall into same memory bank of
    SDRAM chip
  • Calculation
  • Voxel Coord (u,v,w)
  • MiniBlock Coord (um,vm,wm)(u/2,v/2,w/2)
  • Module (umvmwm) mod 4
  • Bank ((um/4)(vm/4)(wm/4)) mod 4

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Voxel Memory (cntd.)
  • Voxel memory must be allocated so all dimentions
    are multiples of 32 voxels
  • Automatic cropping during rendering
  • Arranging voxels in MiniBlocks,
    skewing/deskewing, re-shuffeling and rearranging
    based on view direction are all done by hardware
  • Result
  • Rendering pipelines always have access to 4
    adjacent miniblocks

26
Advanced Features
  • SuperSampling
  • In the Z axis
  • Supervolumes Subvolumes
  • 2563 voxels in one pass
  • Software partitions larger volumes and combines
    results
  • Multiple Subvolumes can be pre-loaded to volume
    memory
  • Subvolumes can be updated in-between frames
  • Dynamic and partial updates to achieve animation
    effects
  • Loading volume in pieces to pan through volume

27
Advanced Features (cntd.)
  • Cropping
  • Multiple clipping planes parallel to volume faces
  • Combination of intersections, unions inverses
  • Cut Planes
  • Single cut plane
  • Arbitrary orientation and thickness
  • Falloff parameter for smooth cuts
  • 3-D cursor
  • Hardware generated
  • Software controlled

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VLI Volume Library Interface
  • VLI API
  • C classes
  • Full access to vg500 chip features
  • Works cooperatively with 3D graphics libarry
    (such as OpenGL)
  • VLI classes
  • Data handling
  • Voxel storage
  • Voxel format
  • Transformations shearing, scaling, positioning

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VLI (cntd.)
  • Rendering elements
  • Color opacity LUTs
  • Lights
  • Cut planes
  • Cropping
  • Etc.
  • Rendering context
  • Specify data set
  • Rendering parameters
  • Much much more

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Future Developments
  • Additional features
  • Perspective projections
  • Intermixing polygons with volume data
  • Additional voxel formats
  • Improvements
  • Increased speed
  • Increased memory
  • Reduced cost
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