Gradient-domain metropolis light transport

  • Authors:
  • Jaakko Lehtinen;Tero Karras;Samuli Laine;Miika Aittala;Frédo Durand;Timo Aila

  • Affiliations:
  • NVIDIA Research and Aalto University;NVIDIA Research;NVIDIA Research;Aalto University and NVIDIA Research;MIT CSAIL;NVIDIA Research

  • Venue:
  • ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
  • Year:
  • 2013

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Abstract

We introduce a novel Metropolis rendering algorithm that directly computes image gradients, and reconstructs the final image from the gradients by solving a Poisson equation. The reconstruction is aided by a low-fidelity approximation of the image computed during gradient sampling. As an extension of path-space Metropolis light transport, our algorithm is well suited for difficult transport scenarios. We demonstrate that our method outperforms the state-of-the-art in several well-known test scenes. Additionally, we analyze the spectral properties of gradient-domain sampling, and compare it to the traditional image-domain sampling.