Abstract

We introduce a novel algorithm for progressively removing noise from view-independent photon maps while simultaneously minimizing residual bias. Our method refines a primal set of photons using data from multiple successive passes to estimate the incident flux local to each photon. We show how this information can be used to guide a relaxation step with the goal of enforcing a constant, per-photon flux. Using a reformulation of the radiance estimate, we demonstrate how the resulting blue noise photon distribution yields a radiance reconstruction in which error is significantly reduced. Our approach has an open-ended runtime of the same order as unbiased and asymptotically consistent rendering methods, converging over time to a stable result. We demonstrate its effectiveness at storing caustic illumination within a view-independent framework and at a fidelity visually comparable to reference images rendered using progressive photon mapping.

Related Files

Pre-print
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Appendix

DOI

10.1145/2421636.2421643
https://dx.doi.org/10.1145/2421636.2421643

Citation

BibTeX

@article{ProgressivePhotonRelaxation,
  author       = {Spencer, Ben and Jones, Mark W.},
  title        = {Progressive Photon Relaxation},
  journal      = {ACM Trans. Graph.},
  volume       = {32},
  number       = {1},
  articleno    = {7},
  pages        = {7:1--7:11},
  date         = {2013-01},
  year         = {2013},
  month        = {jan},
  publisher    = {ACM},
  address      = {New York, NY, USA},
  doi          = {10.1145/2421636.2421643}
}