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
Video
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},
	pages = {7:1--7:11},
	number = {1},
	address = {New York, NY, USA},
	articleno = {7},
	doi = {10.1145/2421636.2421643},
	issue_date = {January 2013},
	publisher = {ACM},
	date={2013-01-01}
}