Volume sampled voxelization of geometric primitives

  • Authors:
  • Sidney W. Wang;Arie E. Kaufman

  • Affiliations:
  • State University of New York at Stony Brook, Stony Brook, NY;State University of New York at Stony Brook, Stony Brook, NY

  • Venue:
  • VIS '93 Proceedings of the 4th conference on Visualization '93
  • Year:
  • 1993

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Abstract

We present a 3D antialiasing algorithm for voxelbased geometric models. The technique band-limits the continuous object before sampling it at the desired 3D raster resolution. By precomputing tables of filter values for different types and sizes of geometric objects, the algorithm is very efficient and has a complexity that is linear with the number of voxels generated. The algorithm not only creates voxel models which are free from object space aliasing, but it also incorporates the image space antialiasing information as part of the view independent voxel model. The resulting alias-free voxel models have been used to model synthetic scenes, for discrete ray tracing applications. The discrete raytraced image is superior in quality to the image generated with a conventional surface-based ray tracer, since silhouettes of objects, shadows, and reflections appear smooth (jaggy-less). In addition, the alias-free models are also suitable for intermixing with sampled datasets, since they can be treated uniformly as one common data representation.