Image-Space Control Variates for Rendering

We propose an image-space (iterative) reconstruction scheme that employs control variates to reduce variance.

We explore the theory of integration with control variates in the context of rendering. Our goal is to optimally combine multiple estimators using their covariances. We focus on two applications, re-rendering, and gradient-domain rendering, where we exploit coherence between temporally and spatially adjacent pixels. We propose an image-space (iterative) reconstruction scheme that employs control variates to reduce variance. We show that recent works on scene editing and gradient-domain rendering can be directly formulated as control-variate estimators, despite using seemingly different approaches. In particular, we demonstrate the conceptual equivalence of screened Poisson image reconstruction and our iterative reconstruction scheme. Our composite estimators offer practical and simple solutions that improve upon the current state of the art for the two investigated applications.