Improved sampling for gradient-domain metropolis light transport

Manzi, Marco; Rousselle, Fabrice; Kettunen, Markus; Lehtinen, Jaakko; Zwicker, Matthias (2014). Improved sampling for gradient-domain metropolis light transport. ACM transactions on graphics, 33(6), pp. 1-12. Association for Computing Machinery 10.1145/2661229.2661291

Preview	Text GMLT_SA14.pdf - Accepted Version Available under License Publisher holds Copyright. © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Graphics, 33(6), http://doi.acm.org/10.1145/2661229.2661291 Download (9MB) | Preview
	Text a178-manzi.pdf - Published Version Restricted to registered users only Available under License Publisher holds Copyright. Download (10MB)

We present a generalized framework for gradient-domain Metropolis rendering, and introduce three techniques to reduce sampling artifacts and variance. The first one is a heuristic weighting strategy that combines several sampling techniques to avoid outliers.
The second one is an improved mapping to generate offset paths required for computing gradients. Here we leverage the properties of manifold walks in path space to cancel out singularities. Finally, the third technique introduces generalized screen space gradient kernels. This approach aligns the gradient kernels with image structures such as texture edges and geometric discontinuities to obtain sparser gradients than with the conventional gradient kernel. We implement our framework on top of an existing Metropolis sampler, and we demonstrate significant improvements in visual and numerical quality of our results compared to previous work.

Interest & Impact

Downloads

174 since deposited on 19 Feb 2015
13 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item