Stratification by Rank-1 Lattices

Alexander Keller ()
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Alexander Keller: University of Ulm, Dept. of Computer Science

A chapter in Monte Carlo and Quasi-Monte Carlo Methods 2002, 2004, pp 299-313 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-18743-8_18

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DOI: 10.1007/978-3-642-18743-8_18

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