Gradient-domain path reusing

Monte-Carlo rendering algorithms have traditionally a high computational cost, because they rely on tracing up to billions of light paths through a scene to physically simulate light transport. Traditional path reusing amortizes the cost of path sampling over multiple pixels, but introduces visually unpleasant correlation artifacts and cannot handle scenes with specular light transport. We present gradient-domain path reusing, a novel unbiased Monte-Carlo rendering technique, which merges the concept of path reusing with the recently introduced idea of gradient-domain rendering. Since correlation is a key element in gradient sampling, it is a natural fit to be performed together with path reusing and we show that the typical artifacts of path reusing are significantly reduced by exploiting the gradient domain. Further, by employing the tools for shifting paths that were designed in the context of gradient-domain rendering over the last years, we can generalize path reusing to support arbitrary scenes including specular light transport. Our method is unbiased and currently the fastest converging unidirectional rendering technique outperforming conventional and gradient-domain path tracing by up to almost an order of magnitude.