I made a new Blender Experiment to explore the possibilities and limits of the new blender denoise function. This time I tested the denoiser on a material using a subsurface shader node in combination with a pretty low sample number, because the subsurface node in a material creates very noisy images and increases render time a lot
you can download the blend file here
For this experiment I creatd a simple is-sphere and added a voronoi texture as the displacement texture to make the object a bit more interesting. The material was created using the new cycles Principled BSDF node.read more ...
Nikos Priniotakis posted a teaser of a denoising script for blender animations a few months ago, that shows really impressive improvements on a noisy cycles animation (see his original tweet here) I sent some twitter messages back and forth with him and he sent me the links to the opencv denoise function he used for the demo. So I finaly found the time to wirte a short python script that uses pyopencv to denoise all the pictures in a folder and copies it to another folder.
The script I used to denoise my animation is here
import cv2 import os import numpy as np from matplotlib import pyplot as plt files = os.listdir("metabubbles/") for f in files: if f.endswith('.png') and f.startswith('0'): print f img = cv2.imread("metabubbles/%s" %f); dst = cv2.fastNlMeansDenoisingColored(img) cv2.imwrite('res/%s' %f, dst);
The denoising process is no magical pixiedust that can be sprinkled on your noisy cycles-renders to fix everything but when used correcly it can improve preview renders a lot, but if the script is used on an image sequence that is too noisy it introduced a whole lot of new artifacts. I used the script on an amiation I rendered last year. Here is how the original video compares to the denoised version.
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