• DocumentCode
    402660
  • Title

    Efficient feed-forward volume rendering techniques for vector and parallel processors

  • Author

    Machiraju, Raghu K. ; Yagel, Roni

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Ohio State Univ., OH, USA
  • fYear
    1993
  • fDate
    15-19 Nov. 1993
  • Firstpage
    699
  • Lastpage
    708
  • Abstract
    Rendering volumes represented as a 3D grid of voxels requires an overwhelming amount of processing power. In this paper we investigate efficient techniques for rendering semi-transparent volumes on vector and parallel processors. Parallelism inherent in a regular grid is obtained by decomposing the volume into geometric primitives called beams, slices and slabs of voxels. By using the adjacent properties of voxels in beams and slices, efficient incremental transformation schemes are developed. The slab decomposition of the volume allows the implementation of an efficient parallel feed-forward renderer which includes the splatting technique for image reconstruction and a back-to-front method for creating images. The authors report the implementation of this feed-forward volume renderer on a hierarchical shared memory machine with individual pipelined processors.
  • Keywords
    feedforward; image reconstruction; parallel processing; pipeline processing; rendering (computer graphics); vector processor systems; 3D grid; adjacent properties; back-to-front method; beams; feed-forward volume rendering; geometric primitives; hierarchical shared memory machine; image creation; image reconstruction; incremental transformation schemes; parallel processors; pipelined processors; regular grid; semitransparent volumes; slabs; slices; splatting technique; vector processors; voxels; Concurrent computing; Feedforward systems; Grid computing; Image reconstruction; Information science; Matrix decomposition; Parallel processing; Pixel; Rendering (computer graphics); Slabs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Supercomputing '93. Proceedings
  • ISSN
    1063-9535
  • Print_ISBN
    0-8186-4340-4
  • Type

    conf

  • DOI
    10.1109/SUPERC.1993.1263524
  • Filename
    1263524