Schuckman, MasonProuty, RoyChapman, DavidEngel, Don2023-06-162023-06-162023-02-15Schuckman, M., Prouty, R., Chapman, D., Engel, D. (2023). Using Moffat Profiles to Register Astronomical Images. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds) Computer Vision – ECCV 2022 Workshops. ECCV 2022. Lecture Notes in Computer Science, vol 13801. Springer, Cham. https://doi.org/10.1007/978-3-031-25056-9_6978-3-031-25056-9https://doi.org/10.1007/978-3-031-25056-9_6http://hdl.handle.net/11603/28224European Conference on Computer Vision, Tel Aviv, Israel, October 23–27, 2022.The accurate registration of astronomical images without a world coordinate system or authoritative catalog is useful for visually enhancing the spatial resolution of multiple images containing the same target. Increasing the resolution of images through super-resolution (SR) techniques can improve the performance of commodity optical hardware, allowing more science to be done with cheaper equipment. Many SR techniques rely on the accurate registration of input images, which is why this work is focused on accurate star finding and registration. In this work, synthetic star field frames are used to explore techniques involving star detection, matching, and transform-fitting. Using Moffat stellar profiles for stars, non-maximal suppression for control-point finding, and gradient descent for point finding optimization, we are able to obtain more accurate transformation parameters than that provided other modern algorithms, e.g., AstroAlign. To validate that we do not over-fit our method to our synthetic images, we use real telescope images and attempt to recover the transformation parameters.16 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Access to this item will begin on 2/15/2025.Text