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A nonrigid registration deep-learning model for solar photosphere images using a hybrid cross-attention mechanism

文献类型：期刊论文

作者Ban, Mengwei1; Wang, Rui1,2; Xu Z(徐稚)3; Liu, Zhongyan1; Nan, Xudong1
刊名Astronomical Techniques and Instruments/天文技术与仪器(英文)
出版日期2026-03
卷号3期号:02
ISSN号1672-7975
DOI10.61977/ati2025043
产权排序第3完成单位
英文摘要Image registration within a solar photosphere sequence is crucial for observational solar physics studies requiring high spatial and temporal resolutions. Previously, we identified residual large-scale nonrigid distortions in high-resolution solar photosphere images from ground-based telescopes after high-resolution reconstruction. Because these distortions are not eliminated by conventional sequence correlation alignment, they can affect the analysis of small-scale activity in the solar photosphere. Here, we implemented an image registration model using deep learning(HCAM-Net) to solve the problem. Within an encoder-decoder framework, we introduced a hybrid attention mechanism to improve context information capture and extract accurate deformation fields. Analyzing solar photosphere images acquired by the New Vacuum Solar Telescope, we demonstrated that the proposed model effectively achieved highly accurate nonrigid image registration. Evaluation metrics and visualization results indicated that our model outperformed current state-of-the-art models, such as VoxelMorph and TransMorph, for nonrigid registration of solar photosphere images, with a structural similarity index measure of 0.965 and a coefficient of determination of 0.976.
学科主题天文学 ; 天文学其他学科 ; 计算机科学技术 ; 计算机应用 ; 计算机图象处理
分类号P182.2
URL标识查看原文
资助项目funded by the Strategic Priority Research Program of the Chinese Academy of Sciences [XDB0560000]; the National Natural Science Foundation of China [12473054]; the Basic Research on Fund Projects in Yunnan Province [2019FA001]; the Yunnan Province Science Foundation Project [202105AC160085]
语种英语
资助机构funded by the Strategic Priority Research Program of the Chinese Academy of Sciences [XDB0560000] ; the National Natural Science Foundation of China [12473054] ; the Basic Research on Fund Projects in Yunnan Province [2019FA001] ; the Yunnan Province Science Foundation Project [202105AC160085]
版本出版稿
源URL[http://ir.ynao.ac.cn/handle/114a53/29136]  
专题无名山观测站
通讯作者Wang, Rui
作者单位1.School of Electronics and Information,Xi'an Polytechnic University;
2.Shaanxi Artificial Intelligence Joint Laboratory,Xi'an Polytechnic University;
3.Yunnan Observatories,Chinese Academy of Sciences
推荐引用方式
GB/T 7714		 Ban, Mengwei,Wang, Rui,Xu Z,et al. A nonrigid registration deep-learning model for solar photosphere images using a hybrid cross-attention mechanism[J]. Astronomical Techniques and Instruments/天文技术与仪器(英文),2026,3(02).
APA Ban, Mengwei,Wang, Rui,徐稚,Liu, Zhongyan,&Nan, Xudong.(2026).A nonrigid registration deep-learning model for solar photosphere images using a hybrid cross-attention mechanism.Astronomical Techniques and Instruments/天文技术与仪器(英文),3(02).
MLA Ban, Mengwei,et al."A nonrigid registration deep-learning model for solar photosphere images using a hybrid cross-attention mechanism".Astronomical Techniques and Instruments/天文技术与仪器(英文) 3.02(2026).

入库方式： OAI收割

来源：云南天文台

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