However, it does provide a way of getting to clean, noise-free output much faster than simply cranking up the sampling settings for a render, and it does so no matter which manufacturer's hardware you use. In addition, OIDN isn't temporally stable, so it isn't suitable for use on animation. These early tests suggest that Blender 2.81's OIDN-based Denoise node is good for quick, approximate work, but that the existing non-AI-based Cycles denoiser preserves fine detail better. Intel's newer Open Image Denoise (OIDN) takes the same approach of speeding up denoising by evolving the algorithms using deep learning, but runs on the CPU, not the GPU - and, crucially for Blender, is available under an Apache 2.0 licence, making it possible to integrate into the software.ĭon't expect miracles. Its OptiX denoiser, now widely integrated into commercial renderers, popularized the idea that, given a large enough set of source renders to work from, denoising algorithms could be trained using machine learning techniques.
We can probably blame NVIDIA for the current vogue for AI-driven denoisers. Open Image Denoise, implemented in Blender 2.81, uses machine learning to train denoising algorithms, making it possible to remove noise from renders faster than simply raising sampling settings.
Blender 2.81 denoise manual#
Over the course of a week-long series of stories, we will preview the main features, continuing today with Open Image Denoise. Blender 2.81 Manual Docs Rendering Layers & Passes Denoising View page source Denoising Reference Panel: Render Layers Denoising Denoising filters the resulting image using information (known as feature passes) gathered during rendering to get rid of noise, while preserving visual detail as well as possible. In this blender tutorial, I show you the new artificial intelligence based image denoising node (denoise node) added to blender 2.81. With the feature list for the next stable version of Blender now locked, we investigate the new tools you can expect when Blender 2.81 ships in November.
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