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Hierarchical Monte Carlo image synthesis

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  • Keller, Alexander

Abstract

A fundamental variance reduction technique for Monte Carlo integration in the framework of integro-approximation problems is presented. Using the method of dependent tests a successive hierarchical function approximation algorithm is developed, which captures discontinuities and exploits smoothness in the target function. The general mathematical scheme and its highly efficient implementation are illustrated for image generation by ray tracing, yielding new and much faster image synthesis algorithms.

Suggested Citation

  • Keller, Alexander, 2001. "Hierarchical Monte Carlo image synthesis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 55(1), pages 79-92.
    • Handle: RePEc:eee:matcom:v:55:y:2001:i:1:p:79-92
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    Cited by:

    1. Keller, Alexander & Dahm, Ken, 2019. "Integral equations and machine learning," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 161(C), pages 2-12.
    2. Holmström, Mats, 2004. "Fast visualization of volume emissions using conservative subdivision," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(6), pages 631-642.

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