![]() The result is known as the bilateral filter, and it’s extremely powerful and flexible, frequently used to remove noise from images. Since edges are a boundary between one group of similar pixels and another group of similarly-coloured pixels, each group’s common shade being quite different, this weight function will preserve edges. There’s an easy fix: add a weight function into the mix, which reduces the contributions of pixels that have different colours. As in, it blurs edges and flat areas equally well. Like nearly all blur filters, though, it suffers from a flaw: it blurs. Speaking of fuzz, you’ve heard of the Gaussian filter, right? It’s a very handy for blurring things and has some interesting mathematical properties. Even if it isn’t, global illumination is notoriously fuzzy so it should still be close enough to fool the eye. ![]() This suggests a cheat: combine together the illumination of nearby pixels that share the same normal, and the result should be similar to cranking the sample count. Bendy things, where the noise is less noticeable, don’t.Īn object’s illumination is very dependent on its surface normal, and nearby patches with the same normal should have similar illumination levels. Notice something interesting, however: flat things tend to have the same surface normal. But another complication is more of an asset: this noise is most noticeable on flat planes which our brain thinks should be smoothed, geometry that’s better known as a “wall.” Worse still, the current trend in 3D is to use indirect diffuse lighting, as it’s what we normally run across in real life. ![]() Not all paths are equal, either, sometimes we’ll take a few extra bounces to reach the source, resulting in less light transferred along that path. The more bounces it takes to connect with a light source, the less likely we’ll stumble onto it by accident conversely, the fewer bounces it takes, the more samples we’ll get at that pixel and the more accurate we’ll calculate its illumination. The other type of noise we’d most like to wipe away comes from indirect diffuse lighting. I’ve covered fireflies in depth already, so I won’t rehash them. If the integrator had more time to sample, the other pixels would find that source too and the difference would disappear. The latter never happens, so we’ll just focus on the first two.įireflies, for instance, are when glossy rays from one pixel connect with a bright light source while neighbouring pixels don’t. Unintended noise when path tracing comes from three possible sources: there aren’t enough sample rays cast into the scene for the integrator to converge on a value, the paths explored miss important light sources, or there’s a bug in the machine. Maybe we can repair bashi’s basic idea? Sources Of Noise The core problem seems to be the combination of the glossy direct and chroma channels, which create noise that throws off the bilateral filter (more on that later). This technique should give better results, though let’s open the hood, and figure out what’s going wrong. The front car’s hood looks great, but the floor is splotchy, the rear car is still noisy, and there’s something terribly wrong with the car seats. ![]() Dang! I fired up Blender, and gave his nodegroup a quick whirl… Had anyone else stumbled on the same technique for removing noise from Cycles renders?Īnswer: yes, in fact “bashi” did it two years ago and without writing a single line of code. #BLENDER CYCLES DENOISE CODE#I was excited to crack open Blender’s source code and start coding, but first I had to do my due diligence. ![]() I think I was half-asleep when I had my “holy shit” moment. ![]()
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