Frequency based kernel estimation for progressive photon mapping

  • Authors:
  • Laurent Belcour;Cyril Soler

  • Affiliations:
  • Grenoble University;Inria

  • Venue:
  • SIGGRAPH Asia 2011 Posters
  • Year:
  • 2011

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Abstract

We present an extension to Hachisuka et al.'s Progressive Photon Mapping (or PPM) algorithm [Hachisuka et al. 2008] in which we estimate the radius of the density estimation kernels using frequency analysis of light transport [Durand et al. 2005]. We predict the local radiance frequency at the surface of objects, and use it to optimize the size of the density estimation kernels, in order to accelerate convergence. The key is to add frequency information to a small proportion of photons: frequency photons. In addition to contributing to the density estimation, they will provide frequency information.