Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration
A few ground-based solar coronagraphs have been installed in western China for observing the low-layer corona in recent years. However, determining the helioprojective coordinates for the coronagraphic data with high precision is an important but challenging step for further research with other mult...
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| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/adf05e |
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| author | Feiyang Sha Yu Liu Lidong Xia Yao Chen Qing Zhou Yangrui Chen Chuyu Zhong Xuefei Zhang Tengfei Song Mingzhe Sun Xiaoyu Yu Haitang Li Jacob Oloketuyi Qiang Liu Xinjian Wang Qiwang Luo Xiaobo Li |
| author_facet | Feiyang Sha Yu Liu Lidong Xia Yao Chen Qing Zhou Yangrui Chen Chuyu Zhong Xuefei Zhang Tengfei Song Mingzhe Sun Xiaoyu Yu Haitang Li Jacob Oloketuyi Qiang Liu Xinjian Wang Qiwang Luo Xiaobo Li |
| author_sort | Feiyang Sha |
| collection | DOAJ |
| description | A few ground-based solar coronagraphs have been installed in western China for observing the low-layer corona in recent years. However, determining the helioprojective coordinates for the coronagraphic data with high precision is an important but challenging step for further research with other multiwavelength data. In this paper, we propose an automatic coronal image registration method that combines local statistical correlation and feature point matching to achieve accurate registration between ground-based coronal green-line images and space-based 211 Å images. Then, the accurate field of view information of the coronal green-line images can be derived, allowing the images to be mapped to the helioprojective Cartesian coordinates with an accuracy of no less than $0\mathop{.}\limits{^{\prime\prime} }1$ . This method has been extensively validated using 100 days of coronal data spanning an 11 yr period, demonstrating its broad applicability to ground-based coronagraphs equipped with green-line observations. It significantly enhances the scientific value of ground-based coronal data, enabling comprehensive studies of coronal transient activities and facilitating the joint analysis of data from multiple instruments. Additionally, it holds potential for future applications in improving the pointing accuracy of coronagraphs. |
| format | Article |
| id | doaj-art-5fffbb976f2a4571a2cc448ae634b7db |
| institution | Kabale University |
| issn | 1538-4357 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astrophysical Journal |
| spelling | doaj-art-5fffbb976f2a4571a2cc448ae634b7db2025-08-25T05:51:25ZengIOP PublishingThe Astrophysical Journal1538-43572025-01-0199015610.3847/1538-4357/adf05eMapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image RegistrationFeiyang Sha0https://orcid.org/0000-0002-2995-070XYu Liu1https://orcid.org/0000-0002-7694-2454Lidong Xia2https://orcid.org/0000-0001-8938-1038Yao Chen3https://orcid.org/0000-0001-6449-8838Qing Zhou4Yangrui Chen5Chuyu Zhong6Xuefei Zhang7https://orcid.org/0000-0002-3828-9837Tengfei Song8https://orcid.org/0000-0002-3876-6330Mingzhe Sun9https://orcid.org/0000-0002-1631-9898Xiaoyu Yu10Haitang Li11https://orcid.org/0000-0001-6024-8399Jacob Oloketuyi12https://orcid.org/0000-0003-2439-2910Qiang Liu13Xinjian Wang14Qiwang Luo15Xiaobo Li16School of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnInstitute of Space Sciences, Shandong University , Weihai 264209, People’s Republic of ChinaSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cn; Institute of Space Sciences, Shandong University , Weihai 264209, People’s Republic of ChinaSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnYunnan Observatories , Chinese Academy of Sciences, Kunming 650216, People’s Republic of ChinaYunnan Observatories , Chinese Academy of Sciences, Kunming 650216, People’s Republic of ChinaInstitute of Space Sciences, Shandong University , Weihai 264209, People’s Republic of ChinaInstitute of Space Sciences, Shandong University , Weihai 264209, People’s Republic of ChinaSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cn; Department of Physics, Bamidele Olumilua University of Education , Science and Technology, Ikere-Ekiti 361251, NigeriaSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnSchool of Physical Science and Technology, Southwest Jiaotong University , Chengdu 611756, People’s Republic of China ; lyu@swjtu.edu.cnYunnan Observatories , Chinese Academy of Sciences, Kunming 650216, People’s Republic of ChinaA few ground-based solar coronagraphs have been installed in western China for observing the low-layer corona in recent years. However, determining the helioprojective coordinates for the coronagraphic data with high precision is an important but challenging step for further research with other multiwavelength data. In this paper, we propose an automatic coronal image registration method that combines local statistical correlation and feature point matching to achieve accurate registration between ground-based coronal green-line images and space-based 211 Å images. Then, the accurate field of view information of the coronal green-line images can be derived, allowing the images to be mapped to the helioprojective Cartesian coordinates with an accuracy of no less than $0\mathop{.}\limits{^{\prime\prime} }1$ . This method has been extensively validated using 100 days of coronal data spanning an 11 yr period, demonstrating its broad applicability to ground-based coronagraphs equipped with green-line observations. It significantly enhances the scientific value of ground-based coronal data, enabling comprehensive studies of coronal transient activities and facilitating the joint analysis of data from multiple instruments. Additionally, it holds potential for future applications in improving the pointing accuracy of coronagraphs.https://doi.org/10.3847/1538-4357/adf05eAstronomy data reductionSolar coronaCoronagraphic imaging |
| spellingShingle | Feiyang Sha Yu Liu Lidong Xia Yao Chen Qing Zhou Yangrui Chen Chuyu Zhong Xuefei Zhang Tengfei Song Mingzhe Sun Xiaoyu Yu Haitang Li Jacob Oloketuyi Qiang Liu Xinjian Wang Qiwang Luo Xiaobo Li Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration The Astrophysical Journal Astronomy data reduction Solar corona Coronagraphic imaging |
| title | Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration |
| title_full | Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration |
| title_fullStr | Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration |
| title_full_unstemmed | Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration |
| title_short | Mapping Ground-based Coronagraphic Images to Helioprojective-Cartesian Coordinate System by Image Registration |
| title_sort | mapping ground based coronagraphic images to helioprojective cartesian coordinate system by image registration |
| topic | Astronomy data reduction Solar corona Coronagraphic imaging |
| url | https://doi.org/10.3847/1538-4357/adf05e |
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