Deep learning image burst stacking to reconstruct high-resolution ground-based solar observations
Schirninger, C., Jarolim, R., Veronig, A. M., Kuckein, C.. (2025). Deep learning image burst stacking to reconstruct high-resolution ground-based solar observations. Astronomy & Astrophysics, doi:https://doi.org/10.1051/0004-6361/202451850
| Title | Deep learning image burst stacking to reconstruct high-resolution ground-based solar observations |
|---|---|
| Genre | Article |
| Author(s) | C. Schirninger, Robert Jarolim, A. M. Veronig, C. Kuckein |
| Abstract | Context. Large aperture ground-based solar telescopes allow the solar atmosphere to be resolved in unprecedented detail. However, ground-based observations are inherently limited due to Earth’s turbulent atmosphere, requiring image correction techniques. |
| Publication Title | Astronomy & Astrophysics |
| Publication Date | Jan 1, 2025 |
| Publisher's Version of Record | https://doi.org/10.1051/0004-6361/202451850 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7m61qkg |
| OpenSky Listing | View on OpenSky |
| CPAESS Affiliations | UCP, SPS |