60 lines
3.1 KiB
Markdown
60 lines
3.1 KiB
Markdown
Open Image Denoise Overview
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===========================
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Intel® Open Image Denoise is an open source library of high-performance,
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high-quality denoising filters for images rendered with ray tracing.
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Open Image Denoise is part of the
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[Intel Rendering Framework](https://software.intel.com/en-us/rendering-framework)
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and is released under the permissive
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[Apache 2.0 license](http://www.apache.org/licenses/LICENSE-2.0).
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The purpose of Open Image Denoise is to provide an open, high-quality,
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efficient, and easy-to-use denoising library that allows one to significantly
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reduce rendering times in ray tracing based rendering applications. It filters
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out the Monte Carlo noise inherent to stochastic ray tracing methods like path
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tracing, reducing the amount of necessary samples per pixel by even multiple
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orders of magnitude (depending on the desired closeness to the ground truth).
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A simple but flexible C/C++ API ensures that the library can be easily
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integrated into most existing or new rendering solutions.
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At the heart of the Open Image Denoise library is an efficient deep learning
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based denoising filter, which was trained to handle a wide range of samples per
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pixel (spp), from 1 spp to almost fully converged. Thus it is suitable for both
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preview and final-frame rendering. The filters can denoise images either using
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only the noisy color (*beauty*) buffer, or, to preserve as much detail as
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possible, can optionally utilize auxiliary feature buffers as well (e.g.
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albedo, normal). Such buffers are supported by most renderers as arbitrary
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output variables (AOVs) or can be usually implemented with little effort.
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Open Image Denoise supports Intel® 64 architecture based CPUs and compatible
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architectures, and runs on anything from laptops, to workstations, to compute
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nodes in HPC systems. It is efficient enough to be suitable not only for
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offline rendering, but, depending on the hardware used, also for interactive
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ray tracing.
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Open Image Denoise internally builds on top of
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[Intel® Math Kernel Library for Deep Neural Networks (MKL-DNN)](https://github.com/intel/mkl-dnn),
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and automatically exploits modern instruction sets like Intel SSE4, AVX2, and
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AVX-512 to achieve high denoising performance. A CPU with support for at least
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SSE4.1 is required to run Open Image Denoise.
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Support and Contact
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-------------------
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Open Image Denoise is under active development, and though we do our best to
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guarantee stable release versions a certain number of bugs, as-yet-missing
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features, inconsistencies, or any other issues are still possible. Should you
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find any such issues please report them immediately via the
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[Open Image Denoise GitHub Issue Tracker](https://github.com/OpenImageDenoise/oidn/issues)
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(or, if you should happen to have a fix for it, you can also send us a pull
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request); for missing features please contact us via email at
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<openimagedenoise@googlegroups.com>.
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For recent news, updates, and announcements, please see our complete
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[news/updates] page.
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Join our [mailing list](https://groups.google.com/d/forum/openimagedenoise/) to
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receive release announcements and major news regarding Open Image Denoise.
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