Nowaday CG Artist is quite familiar with the word: Denoise. De-noising is a vital post-processing component of ray-traced images, as it eliminates visual noise generated by too few rays intersecting pixels that make up an image. In an ideal world, a ray should hit every pixel on the screen, but in the real world, computing hasn't advanced enough to do that in reasonable/real-time. Denoising attempts to correct and reconstruct such images. Intel has unveiled its free Open Image Denoise (OIDN) - a collection 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).
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 fully exploits modern instruction sets like Intel SSE4, AVX2, and AVX-512 to achieve high denoising performance. A CPU with support for at least SSE4.2 is required to run Open Image Denoise.
Open Image Denoise is under active development, if you find some bugs or any such issues you can support to report them via the Open Image Denoise GitHub Issue Tracker, for missing features please contact developer via email at openimagedenoise@googlegroups.com. More information here!
[post_ads_2]