EGU24-15813, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Instrument-to-Instrument translation: An AI tool to intercalibrate, enhance and super-resolve solar observations

Christoph Schirninger1, Astrid Veronig1,2, Robert Jarolim3, J. Emmanuel Johnson4, Anna Jungbluth5, Richard Galvez6, Lilli Freischem7, and Anne Spalding6
Christoph Schirninger et al.
  • 1Institute of Physics, University of Graz, Austria
  • 2Kanzelhöhe Observatory for Solar and Environmental Research, University of Graz, Austria
  • 3High Altitude Observatory, Boulder, USA
  • 4Institut des Géosciences de l'Environnement (MEOM), CNRS, France
  • 5European Space Agency - ESA
  • 6Trillium Technologies, Inc, USA
  • 7Department of Physics, University of Oxford, UK

Various instruments are used to study the Sun, including ground-based observatories and space telescopes. These data products are constantly changing due to technological improvements, different instrumentation, or atmospheric effects. However, for certain applications such as ground-based solar image reconstruction or solar cycle studies, enhanced and combined data products are necessary.

We present a general AI tool called Instrument-to-Instrument (ITI; Jarolim et al. 2023) translation, which is capable of translating datasets between two different image domains. This approach enables instrument intercalibration, image enhancement, mitigation of quality degradations, and super-resolution across multiple wavelength bands. The tool is built on unpaired image-to-image translation, which enables a wide range of applications, where no spatial or temporal overlap is required between the considered datasets.

In this presentation, we highlight ITI as a general tool for Heliospheric applications and demonstrate its capabilities by applying it to data from Solar Orbiter/EUI, PROBA2/SWAP, and the Solar Dynamics Observatory/AIA in order to achieve a homogenous, machine-learning ready dataset that combines three different EUV imagers. 

The direct comparison of aligned observations shows the close relation of ITI-enhanced and real high-quality observations. The evaluation of light-curves demonstrates an improved inter-calibration.

ITI is provided open-source to the community  and can be easily applied to novel datasets and various research applications. 

This research is funded through a NASA 22-MDRAIT22-0018 award (No 80NSSC23K1045) and managed by Trillium Technologies, Inc (

How to cite: Schirninger, C., Veronig, A., Jarolim, R., Johnson, J. E., Jungbluth, A., Galvez, R., Freischem, L., and Spalding, A.: Instrument-to-Instrument translation: An AI tool to intercalibrate, enhance and super-resolve solar observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15813,, 2024.