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Photon differentials

Published: 01 December 2007 Publication History

Abstract

A number of popular global illumination algorithms uses density estimation to approximate indirect illumination. The density estimate is performed on finite points -- particles -- generated by a stochastic sampling of the scene. In the course of the sampling, particles, representing light, are stochastically emitted from the light sources and reflected around the scene. The sampling induces noise, which in turn is handled by the density estimate during the illumination reconstruction. Unfortunately, this noise reduction imposes a systematic error (bias), which is seen as a blurring of prominent illumination features. This is often not desirable as these may lose clarity or vanish altogether.
We present an accurate method for reconstruction of indirect illumination with photon mapping. Instead of reconstructing illumination using classic density estimation on finite points, we use the correlation of light footprints, created by using Ray Differentials during the light pass. This procedure gives a high illumination accuracy, improving the trade-off between bias and variance considerable as compared to traditional particle tracing algorithms. In this way we preserve structures in indirect illumination.

References

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cover image ACM Conferences
GRAPHITE '07: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
December 2007
335 pages
ISBN:9781595939128
DOI:10.1145/1321261
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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Published: 01 December 2007

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Author Tags

  1. caustics
  2. global illumination
  3. photon mapping
  4. ray differentials
  5. ray-tracing

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  • (2020)Deep Kernel Density Estimation for Photon MappingComputer Graphics Forum10.1111/cgf.1405239:4(35-45)Online publication date: 20-Jul-2020
  • (2019)A Task and Data Balanced Distributed Photon Mapping MethodComputers & Graphics10.1016/j.cag.2019.05.009Online publication date: May-2019
  • (2018)Second-Order Occlusion-Aware Volumetric Radiance CachingACM Transactions on Graphics10.1145/318522537:2(1-14)Online publication date: 2-Jul-2018
  • (2018)Efficient Caustic Rendering with Lightweight Photon MappingComputer Graphics Forum10.1111/cgf.1348137:4(133-142)Online publication date: 20-Jul-2018
  • (2017)Antialiasing Complex Global Illumination Effects in Path-SpaceACM Transactions on Graphics10.1145/3072959.299049536:4(1)Online publication date: 16-Jul-2017
  • (2017)Antialiasing Complex Global Illumination Effects in Path-SpaceACM Transactions on Graphics10.1145/299049536:1(1-13)Online publication date: 6-Jan-2017
  • (2015)A Visualization Tool Used to Develop New Photon Mapping TechniquesComputer Graphics Forum10.1111/cgf.1246434:1(127-140)Online publication date: 1-Feb-2015
  • (2015)Spectral caustic rendering of a homogeneous caustic object based on wavelength clustering and eye sensitivityThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-014-1037-z31:12(1601-1614)Online publication date: 1-Dec-2015
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