Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anuta, P.E.: Spatial registration of multispectral and multitemporal digital imagery using fast fourier transform techniques. IEEE Trans. Geosci. Electron. 8(4), 353–368 (1970). https://doi.org/10.1109/TGE.1970.271435
Bannore, V.: Iterative-Interpolation Super-Resolution Image Reconstruction, A Computationally Efficient Technique. Studies in Computational Intelligence, pp. 77–91 (2009). https://doi.org/10.1007/978-3-642-00385-1_5
Beroiz, M., Cabral, J., Sanchez, B.: Astroalign: a python module for astronomical image registration. Astron. Comput. 32, 100384 (2020). https://doi.org/10.1016/j.ascom.2020.100384
Bradski, G.: The OpenCV library. Dr. Dobb’s J. Softw. Tools (2000)
Gómez, J.L., et al.: Probing the innermost regions of AGN jets and their magnetic fields with RadioAstron. I. Imaging BL Lacertae at 21 microarcsecond resolution. arXiv (2015)
Greisen, E.W., Calabretta, M.R.: Representations of world coordinates in fits. Astron. Astrophys. 395(3), 1061–1075 (2002). https://doi.org/10.1051/0004-6361:20021326
Gural, P.S., Larsen, J.A., Gleason, A.E.: Matched filter processing for asteroid detection. Astron. J. 130(4), 1951–1960 (2005). https://doi.org/10.1086/444415
Gural, P.S., Otto, P.R., Tedesco, E.F.: Moving object detection using a parallax shift vector algorithm. Publ. Astron. Soc. Pac. 130(989), 074504 (2018). https://doi.org/10.1088/1538-3873/aac1ff
Keating, T.J., Wolf, P.R., Scarpace, F.: An improved method of digital image correlation. Photogramm. Eng. Remote Sens. 41, 993–1002 (1975)
King, B.: 9,096 stars in the sky - is that all? (2014). https://skyandtelescope.org/astronomy-blogs/how-many-stars-night-sky-09172014/
King, B.: The eyes have it - deep-sky observing without equipment (2018). https://skyandtelescope.org/observing/deep-sky-naked-eye/
Lang, D., Hogg, D.W., Mierle, K., Blanton, M., Roweis, S.: Astrometry.net: blind astrometric calibration of arbitrary astronomical images. Astron. J. 139(5), 1782–1800 (2010). https://doi.org/10.1088/0004-6256/139/5/1782
Li, Z., Peng, Q., Bhanu, B., Zhang, Q., He, H.: Super resolution for astronomical observations. Astrophys. Space Sci. 363(5), 1–15 (2018). https://doi.org/10.1007/s10509-018-3315-0
Loke, S.C.: Astronomical image acquisition using an improved track and accumulate method. IEEE Access 5, 9691–9698 (2017). https://doi.org/10.1109/access.2017.2700162
Mandel, J., Beezley, J., Coen, J., Kim, M.: Data assimilation for wildland fires. IEEE Control. Syst. 29(3), 47–65 (2009). https://doi.org/10.1109/mcs.2009.932224
Marois, C., Macintosh, B., Véran, J.P.: Exoplanet imaging with LOCI processing: photometry and astrometry with the new SOSIE pipeline. In: Adaptive Optics Systems II, pp. 77361J–77361J-12 (2010). https://doi.org/10.1117/12.857225
Moffat, A.F.J.: A theoretical investigation of focal stellar images in the photographic emulsion and application to photographic photometry. Astron. Astrophys. (1969). https://ui.adsabs.harvard.edu/abs/1969A &A....3.455M
Rieke, G.H., et al.: The mid-infrared instrument for the James Webb space telescope, VII: the MIRI detectors. Publ. Astron. Soc. Pac. 127(953), 665–674 (2015). https://doi.org/10.1086/682257
Shahhosseini, S., Rezaie, B., Emamian, V.: Sequential image registration for astronomical images. In: 2012 IEEE International Symposium on Multimedia, pp. 314–317 (2012). https://doi.org/10.1109/ISM.2012.65
Stahl, H.P.: Survey of cost models for space telescopes. Opt. Eng. 49(5), 053005–053005-8 (2010). https://doi.org/10.1117/1.3430603
Stone, E., Bolte, M.: Development of the thirty-meter telescope project. Curr. Sci. 113(04), 628–630 (2017). https://doi.org/10.18520/cs/v113/i04/628-630
Tabur, V.: Fast algorithms for matching CCD images to a stellar catalogue. Publ. Astron. Soc. Aust. 24(4), 189–198 (2007). https://doi.org/10.1071/AS07028
Trujillo, I., Aguerri, J., Cepa, J., Gutiérrez, C.: The effects of seeing on Sérsic profiles - II. The Moffat PSF. Mon. Not. R. Astron. Soc. 328(3), 977–985 (2001). https://doi.org/10.1046/j.1365-8711.2001.04937.x
Zitová, B., Flusser, J.: Image registration methods: a survey. Image Vis. Comput. 21(11), 977–1000 (2003). https://doi.org/10.1016/s0262-8856(03)00137-9
Acknowledgements
The material is based upon work supported by NASA under award number 80GSFC21M0002 and by a UMBC Undergraduate Research Award.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Schuckman, 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_6
Download citation
DOI: https://doi.org/10.1007/978-3-031-25056-9_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-25055-2
Online ISBN: 978-3-031-25056-9
eBook Packages: Computer ScienceComputer Science (R0)