Intel® Open Image Denoise

High-Performance Denoising Library for Ray Tracing

Denoised
Original

Moana Island Scene rendered at 16 spp with Intel® OSPRay and denoised with Intel® Open Image Denoise. Publicly available dataset courtesy of Walt Disney Animation Studios. Hover over the image (or tap on it) to move the slider between the original and denoised versions.

Open Image Denoise Overview

Intel® Open Image Denoise is an open source library of high-performance, high-quality denoising filters for images rendered with ray tracing. Open Image Denoise is part of the Intel Rendering Framework and is released under the permissive Apache 2.0 license.

The purpose of Open Image Denoise is to provide an open, high-quality, efficient, and easy-to-use denoising library that allows one to significantly reduce rendering times in ray tracing based rendering applications. It filters out the Monte Carlo noise inherent to stochastic ray tracing methods like path tracing, reducing the amount of necessary samples per pixel by even multiple orders of magnitude (depending on the desired closeness to the ground truth). A simple but flexible C/C++ API ensures that the library can be easily integrated into most existing or new rendering solutions.

At the heart of the Open Image Denoise library is an efficient deep learning based denoising filter, which was trained to handle a wide range of samples per pixel (spp), from 1 spp to almost fully converged. Thus it is suitable for both preview and final-frame rendering. The filters can denoise images either using only the noisy color (beauty) buffer, or, to preserve as much detail as possible, can optionally utilize auxiliary feature buffers as well (e.g. albedo, normal). Such buffers are supported by most renderers as arbitrary output variables (AOVs) or can be usually implemented with little effort.

Open Image Denoise supports Intel® 64 architecture based CPUs and compatible architectures, and runs on anything from laptops, to workstations, to compute nodes in HPC systems. It is efficient enough to be suitable not only for offline rendering, but, depending on the hardware used, also for interactive ray tracing.

Open Image Denoise internally builds on top of Intel® Math Kernel Library for Deep Neural Networks (MKL-DNN), and automatically exploits modern instruction sets like Intel SSE4, AVX2, and AVX-512 to achieve high denoising performance. A CPU with support for at least SSE4.1 is required to run Open Image Denoise.

Support and Contact

Open Image Denoise is under active development, and though we do our best to guarantee stable release versions a certain number of bugs, as-yet-missing features, inconsistencies, or any other issues are still possible. Should you find any such issues please report them immediately via the Open Image Denoise GitHub Issue Tracker (or, if you should happen to have a fix for it, you can also send us a pull request); for missing features please contact us via email at .

For recent news, updates, and announcements, please see our complete news/updates page.

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Version History

Changes in v0.9.0:

Changes in v0.8.2:

Changes in v0.8.1:

Changes in v0.8.0: