Here Ill show you a way to get rid of that noise using the selective Gaussian blur filter.

You could think of it like the opposite of unsharpen mask (that sharpens everything with contrast above a certain threshold.

Select the crop tool from the tool box, draw a selection and click crop.

In short, maximum delta should be just high enough for the filter to kick in on the noise and blur radius should be just high enough to remove it (actually blend it with neighboring areas).

Then I checked what those settings looked like on another crop (which is always a good idea to do), I decided that it was on the very edge, and maybe even too much.

All I can say is that you develop a feel for it, and Im still not finished developing that feel.

In any case, its good to know that the first things that start to look funny are often faces and hair.

A method for estimating the noise level of an image with knowing the ground truth.

A dataset of pixel and brightness aligned noisy and low noise images.

An evaluation of six image denoising methods on this dataset.

Abstract Image denoising algorithms are evaluated using images corrupted by artificial noise, which may lead to incorrect conclusions about their performances on real noise.

In this paper we introduce a dataset of color images corrupted by natural noise due to low-light conditions, together with spatially and intensity-aligned low noise images of the same scenes.

We also introduce a method for estimating the true noise level in our images, since even the low noise images contain small amounts of noise.

We evaluate the accuracy of our noise estimation method on real and artificial noise, and investigate the Poisson-Gaussian noise model.

Finally, we use our dataset to evaluate six denoising algorithms: Active Random Field, BM3D, Bilevel-MRF, Multi-Layer Perceptron, and two versions of NL-means.

We show that while the Multi-Layer Perceptron, Bilevel-MRF, and NL-means with soft threshold outperform BM3D on gray images with synthetic noise, they lag behind on our dataset.

Previous article in issue Next article in issue Keywords Image denoising Denoising dataset Low light noise Poisson-Gaussian noise model Recommended articles Citing articles (0) This paper has been recommended for acceptance by Zicheng Liu.

Citing articles Article Metrics View article metrics About ScienceDirect Remote access Shopping cart Advertise Contact and support Terms and conditions Privacy policy We use cookies to help provide and enhance our service and tailor content and ads.

ScienceDirect is a registered trademark of Elsevier B.V.

Krita Gaussian Noise Reduction