Home

Awesome

FidelityFX Denoiser

Copyright (c) 2021 Advanced Micro Devices, Inc. All rights reserved. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Overview

FidelityFX Denoiser contains a collection of highly optimized denoiser implementations for specific use cases.

FidelityFX Shadow Denoiser

A spatio-temporal denoiser for raytraced soft shadows. It is intended to be used on a shadow mask that was created from at most one jittered shadow ray per pixel. It makes use of a tile classification pass to skip work on areas without spatial variance in the shadow mask. In cases of low temporal sample counts, the contribution from the spatial filters are increased, which successively cools off as the temporal sample count increases. The denoiser aims to avoid ghosting artifacts by analyzing the local pixel neighborhood and clamping the accumulated history.

Links

FidelityFX Reflection Denoiser

The reflection denoiser includes a high performance spatio-temporal denoiser specialized for reflection denoising. The preferred use case of this denoiser is within applications requiring denoised radiance values generated by some stochastic reflection implementation. Examples of stochastic reflections:

Links