Robust Denoising using Feature and Color Information

@article{Rousselle2013RobustDU,
  title={Robust Denoising using Feature and Color Information},
  author={Fabrice Rousselle and Marco Manzi and Matthias Zwicker},
  journal={Comput. Graph. Forum},
  year={2013},
  volume={32},
  pages={121-130}
}
We propose a method that robustly combines color and feature buffers to denoise Monte Carlo renderings. On one hand, feature buffers, such as per pixel normals, textures, or depth, are effective in determining denoising filters because features are highly correlated with rendered images. Filters based solely on features, however, are prone to blurring image details that are not well represented by the features. On the other hand, color buffers represent all details, but they may be less… CONTINUE READING
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