Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 12
Articles | Volume 19, issue 12
https://doi.org/10.5194/amt-19-3999-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-3999-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 12
Research article
 | 
17 Jun 2026
Research article |  | 17 Jun 2026

Bayesian denoising of satellite images using co-registered NO2 images

Erik Franciscus Maria Koene, Gerrit Kuhlmann, and Dominik Brunner

Viewed

Total article views: 2,839 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,823 816 200 2,839 351 144 190
  • HTML: 1,823
  • PDF: 816
  • XML: 200
  • Total: 2,839
  • Supplement: 351
  • BibTeX: 144
  • EndNote: 190
Views and downloads (calculated since 13 Oct 2025)
Cumulative views and downloads (calculated since 13 Oct 2025)

Viewed (geographical distribution)

Total article views: 2,839 (including HTML, PDF, and XML) Thereof 2,832 with geography defined and 7 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 Jun 2026
Download
Short summary
We developed methods to reduce noise in satellite images that track air pollution. By using clearer measurements of a related gas, our techniques improve image quality by up to 80 percent, allowing more accurate identification of pollution sources. Tested with simulated and real satellite data, this approach could enhance monitoring of emissions and support better environmental decisions.
Read more
Share