Practical Reconstruction Schemes and Hardware-Accelerated Direct Volume Rendering on Body-Centered Cubic Grids

Oliver Mattausch
Practical Reconstruction Schemes and Hardware-Accelerated Direct Volume Rendering on Body-Centered Cubic Grids
[Thesis]

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Abstract

It is well known in the signal-processing community that the Body-Centered Cubic grid is the optimal sampling grid in 3D. In volume visualization, the Cartesian grid is by far the most popular type of grid because it is convenient to handle. But it requires 29.3% more samples than the Body-Centered Cubic grid. In order to convince people used to Cartesian grids for years of the advantages of Body-Centered Cubic grids, we must prove their usability in many different volume rendering algorithms. Further we have to show that we get a performance gain without or with only slight loss of image quality compared to Cartesian grids. Therefore we introduce several practical reconstruction schemes on Body-Centered Cubic grids, which are very general and can be used in a number of applications and tasks. Together with the development of powerful and flexible consumer graphics hardware, interactive hardware-accelerated volume rendering algorithms gain popularity. Rendering performance becomes a big issue, which can be a strong argument in favour of Body-Centered Cubic grids. We adapted some of the most popular volume rendering approaches exploiting hardwareacceleration to Body-Centered Cubic grids: both 2D and 3D texture-based volume rendering and the projected tetrahedra algorithm. At least partly we succeeded in achieving a performance gain on our new grid and further produced some impressive rendering results comparable to the Cartesian grid version.

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BibTeX

@mastersthesis{matt-masterthesis,
  title =      "Practical Reconstruction Schemes and Hardware-Accelerated
               Direct Volume Rendering on Body-Centered Cubic Grids",
  author =     "Oliver Mattausch",
  year =       "2004",
  abstract =   "It is well known in the signal-processing community that the
               Body-Centered Cubic grid is the optimal sampling grid in 3D.
               In volume visualization, the Cartesian grid is by far the
               most popular type of grid because it is convenient to
               handle. But it requires 29.3% more samples than the
               Body-Centered Cubic grid. In order to convince people used
               to Cartesian grids for years of the advantages of
               Body-Centered Cubic grids, we must prove their usability in
               many different volume rendering algorithms. Further we have
               to show that we get a performance gain without or with only
               slight loss of image quality compared to Cartesian grids.
               Therefore we introduce several practical reconstruction
               schemes on Body-Centered Cubic grids, which are very general
               and can be used in a number of applications and tasks.
               Together with the development of powerful and flexible
               consumer graphics hardware, interactive hardware-accelerated
               volume rendering algorithms gain popularity. Rendering
               performance becomes a big issue, which can be a strong
               argument in favour of Body-Centered Cubic grids. We adapted
               some of the most popular volume rendering approaches
               exploiting hardwareacceleration to Body-Centered Cubic
               grids: both 2D and 3D texture-based volume rendering and the
               projected tetrahedra algorithm. At least partly we succeeded
               in achieving a performance gain on our new grid and further
               produced some impressive rendering results comparable to the
               Cartesian grid version.",
  month =      may,
  note =       "1",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2004/matt-masterthesis/",
}