10.5061/DRYAD.CVDNCJT5F
McFadden, David
0000-0001-7446-4914
Friedrich Schiller University Jena
Amos, Brad
MRC Laboratory of Molecular Biology
Heintzmann, Rainer
0000-0002-4950-1936
Leibniz Institute of Photonic Technology
Data supplement to: Quality control of image sensors using gaseous tritium
light sources
Dryad
dataset
2021
FOS: Physical sciences
gain
camera calibration
betalight
CCD
scmos
Deutsche Forschungsgemeinschaft
https://ror.org/018mejw64
1278 Polytarget, Project C04
2022-02-11T00:00:00Z
2022-02-11T00:00:00Z
en
https://github.com/mcfaddendavid/betalight-calibration
https://gitlab.com/bionanoimaging/nanoimagingpack/
https://doi.org/10.6084/m9.figshare.c.5768142
https://doi.org/10.5281/zenodo.5738630
4554815112 bytes
5
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
In the article “Quality Control of Image Sensors using Gaseous Tritium
Light Sources” (https://doi.org/10.1098/rsta.2021.0130) we propose a
practical method for radiometrically calibrating cameras using widely
available gaseous tritium light sources (betalights). This dataset
includes all the recorded data along with the scripts necessary to
reproduce the results and figures.
The raw data consisting of stacks of calibration images, spectral data,
and photodiode readings were acquired according to the method described in
the publication. Tabular data on spectral responsivity were manually read
from graphical plots that were included in the camera brochures or quality
control reports. Some images may have been converted from one lossless
format to lossless tiff files in order to read and process the data. Some
image sequences may have been converted to a 3D stack and vice versa.
All processing is done in the .ipynb notebook script
(https://doi.org/10.5281/zenodo.5738630). This should be consulted for
details about the processing environment and processing steps. The
individual steps are commented and figures are saved to an output
directory. For convenient viewing, there is also an HTML rendering of the
notebook. The "data.zip" archive should be unpacked. When
"evaluation_notebook.ipynb" is run, it expects to find the
"data" subdirectory. run_directory/ ├──
evaluation_notebook.ipynb └── data/ ├── attenuation_experiment/ └──
... The notebook uses our publically available "NanoImagingPack"
library, available at https://gitlab.com/bionanoimaging/nanoimagingpack/ .
Installation instructions are provided there. The package has some
additional dependencies that are available from Anaconda. The script was
run with code on the following commit:
489080ad8981110f0e1ac043f9952a86827afeb The included readme file describes
the individual files in more detail.