How to create camera noise profiles for darktable
An easy way to create correct profiling pictures
By Andreas Schneider
15 Apr 2018
[Article updated on: 2019-11-26]
What is noise?
Noise in digital images is similar to film grain in analogue photography. In digital cameras, noise is either created by the amplification of digital signals or heat produced by the sensor. It appears as random, colored speckles on an otherwise smooth surface and can significantly degrade image quality.
Noise is always present, and if it gets too pronounced, it detracts from the image and needs to be mitigated. Removing noise can decrease image quality or sharpness. There are different algorithms to reduce noise, but the best option is if having profiles for a camera to understand the noise patterns a camera model produces.
Noise reduction is an image restoration process. You want to remove the digital artifacts from the image in such a way that the original image is discernible. These artifacts can be just some kind of grain (luminance noise) or colorful, disturbing dots (chroma noise). It can either add to a picture or detract from it. If the noise is disturbing, we want to remove it. The following pictures show a picture with noise and a denoised version:
To get the best noise reduction, we need to generate noise profiles for each ISO value for a camera.
Creating the pictures for noise profiling
For every ISO value your camera has, you have to take a picture. The pictures need to be exposed a particular way to gather the information correctly. The photos need to be out of focus with a widespread histogram like in the following image:
We need overexposed and underexposed areas, but mostly particularly the grey areas in between. These areas contain the information we are looking for.
Let’s go through the noise profile generation step by step. For easier creation of the required pictures, we will create a stencil which will make it easier to capture the photos.
Building a profiling testbed
Requiements
- A dark room (wait till night time)
- Monitor
- Printer
- Sheets of black thick paper (DIN A3, >= 200g/m²)
- White paper
- Scissors
- Sellotape (Tesafilm)
First you need to get some thicker black paper or cardboard. No light should shine through it! Then you need to print out a gradient on white paper. Light should shine through the white paper!
Print this black to white gradient (PDF)
I got black thick paper (DIN A3, >= 200g/m²) and used two sheets. You need to be able to cover your monitor with the black paper. Put the printed gradient in the middle and draw around it. From three sides (bottom, left, top) make the window smaller by 1 cm, see Figure 1. On the right we need to have a gap.
Next is to cut out the window and type the gradient onto the black paper like in Figure 2. It is important that there is a gap between the white and the black paper on the white side of the gradient. We need light for an overexposed area.
Once you have done that go to your monitor and make it all white. You can an all white image for that. Then tape the sheets to your monitor like in Figure 3.
Taking the pictures
It is time to get your camera. You need to shoot in RAW. It is best to turn off any noise reduction especially long exposure noise reduction. Mount the camera on a tripod and use a lens between 35 mm to 85 mm (full frame). I used a 85 mm f/1.4 lens.
Make sure the gradient fills most of the frame. Set your camera to manual focus and focus on infinity. Select the manual mode of your camera and choose the fastest aperture and ISO100. Depending on the lens you’re using you might want to close the aperture. For me f/1.4 was too blurry and I closed it till f/4.0. You don’t want to see any edges or any structure on the paper but be too blurry. You want to still see the gradient but we want nice transitions between different lightning zone black -> grey -> white like in Figure 4.
Now you need to set the shutter speed. Make the picture really dark and then make the shutter speed longer till the gap which gives us the white from the monitor is overexposed, pure white see Figure 4. The black around the white paper should be underexposed (pure black).
Now you need to take a picture for each ISO value of your camera. When you increase the ISO value you need to decrease the shutter speed!
Creating the noise profiles
STEP 1
Run
/usr/lib/darktable/tools/darktable-gen-noiseprofile --help
If this gives you the help of the tool, continue with STEP 2 otherwise go to STEP 1a. Packages for openSUSE, Fedora, Ubuntu and Debian packaging the noise tools can be found here .
STEP 1a
Your darktable installation doesn’t offer the noise tools so you need to compile it yourself. Before you start make sure that you have the following dependencies installed on your system:
- git
- gcc
- make
- gnuplot
- convert (ImageMagick)
- darktable-cli
Get the darktable source code using git:
git clone https://github.com/darktable-org/darktable.git
Now change to the source and build the tools for creating noise profiles using:
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=/opt/darktable -DBUILD_NOISE_TOOLS=ON ..
cd tools/noise
make
sudo make install
STEP 2
Download the pictures from your camera and change to the directory on the command line:
cd /path/to/noise_pictures
and run the following command:
/usr/lib/darktable/tools/darktable-gen-noiseprofile -d $(pwd)
or if you had to download and build the source, run:
/opt/darktable_source/lib/tools/darktable-gen-noiseprofile -d $(pwd)
This will automatically do everything for you. Note that this can take quite some time to finish. I think it took 15 to 20 minutes on my machine. If a picture is not exposed correctly, the tool will tell you the image name and you have to recapture the picture with that ISO. Remove the non-working picture.
The tool will tell you, once completed, how to test and verify the noise profiles you created.
Once the tool finished, you end up with a tarball you can send to darktable for inclusion. You can open a bug here
The interesting files are the presets.json
file (darktable input) and, for the
developers, the noise_result.pdf file. You can find an example PDF
here
. It is a
collection of diagrams showing the histogram for each picture and the results
of the calculations.
A detailed explanation of the diagrams and the math behind it can be found in the original noise profile tutorial by Johannes Hanika.
Feedback is very much welcome in the comments below!