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Wavelet importance sampling: efficiently evaluating products of complex functions

Published: 01 July 2005 Publication History

Abstract

We present a new technique for importance sampling products of complex functions using wavelets. First, we generalize previous work on wavelet products to higher dimensional spaces and show how this product can be sampled on-the-fly without the need of evaluating the full product. This makes it possible to sample products of high-dimensional functions even if the product of the two functions in itself is too memory consuming. Then, we present a novel hierarchical sample warping algorithm that generates high-quality point distributions, which match the wavelet representation exactly. One application of the new sampling technique is rendering of objects with measured BRDFs illuminated by complex distant lighting --- our results demonstrate how the new sampling technique is more than an order of magnitude more efficient than the best previous techniques.

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cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 24, Issue 3
July 2005
826 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/1073204
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 July 2005
Published in TOG Volume 24, Issue 3

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Author Tags

  1. Monte Carlo techniques
  2. complex products
  3. global illumination
  4. importance sampling
  5. rendering
  6. wavelets

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