The goal of this project is to implement an optional denoising step in Cycles, which would be executed between the actual pathtracing and the Compositor and remove remaining noise from the image, at the cost of some accuracy.

In the last few years, a lot of great research regarding denoising the output of pathtracers has been published, but these algorithms rely on additional information provided by the renderer, which makes an integration in the Compositor very memory-intensive and a challenge in UI design.

Because of that, this proposal is about having a denoiser right in Cycles - where all the additional information (like feature passes and variance info) is available and can be used to produce results that are far better than general image denoising, often allowing to cut render times by 75% or more.

The workflow will be as simple as possible: An additional panel in the rendering properties will allow to switch denoising on and off, along with further options for advanced users to fine-control the behavior of the filter.

Organization

Student

Lukas Stockner

Mentors

  • Sergey Sharybin
close

2016