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Stratification by Rank-1 Lattices

  • Alexander Keller
Conference paper

Summary

Many rendering problems can only be solved using Monte Carlo integration. The noise and variance inherent with the statistical method efficiently can be reduced by stratification. So far only uncorrelated stratification methods were used, where in addition the number of strata exponentially depends on the dimension of the integration domain. Based on rank-1 lattices we present a new stratification technique that removes this dependency on dimension. It is much more efficient by correlation, trivial to implement, and robust to use. The superiority of the new scheme is demonstrated for standard rendering algorithms.

Keywords

Computer Graphic Latin Hypercube Sample Correlate Sampling Monte Carlo Integration Eurographics Workshop 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alexander Keller
    • 1
  1. 1.Dept. of Computer ScienceUniversity of UlmUlmGermany

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