SolarZip: An efficient and adaptive compression framework for Solar EUV imaging data: Application to Solar Orbiter/EUI data

doi:10.1051/0004-6361/202555193

	SolarZip: An efficient and adaptive compression framework for Solar EUV imaging data: Application to Solar Orbiter/EUI data
	Liu, Zedong 1,2,5; Tan, Song 3,4; Warmuth, Alexander 3; Schuller, Frederic 3; Hong, Yun 6; Huang, Wenjing 1,5; Gu, Yida 1,5; Zhu, Bojing 5,7,8; Tan, Guangming 1,5; Tao, Dingwen 1,5
	2025-10-01
发表期刊	ASTRONOMY & ASTROPHYSICS
ISSN	0004-6361
卷号	702 页码:17
摘要	Context. With the advancement of solar physics research, next-generation solar space missions and ground-based telescopes face significant challenges in efficiently transmitting and/or storing large-scale observational data. Aims. We have developed an efficient compression and evaluation framework for solar EUV data, specifically optimized for Solar Orbiter Extreme Ultraviolet Imager (EUI) data. It significantly reduces the data volume, while preserving scientific usability. Methods. We evaluated four error-bounded lossy compressors across two Solar Orbiter/EUI datasets spanning 50 months of observations. However, existing methods cannot perfectly handle the EUV data. Building on this analysis, we developed SolarZip, an adaptive compression framework featuring: (1) a hybrid strategy controller that dynamically selects the optimal compression strategy; (2) enhanced spline interpolation predictors with grid-wise anchor points and level-wise error bound auto-tuning; and (3) a comprehensive two-stage evaluation methodology integrating standard distortion metrics with domain-specific post hoc scientific analyses. Results. Our SolarZip framework achieved a data compression ratio of up to 800x for Full Sun Imager (FSI) data and 500x for High Resolution Imager (HRIEUV) data. It significantly outperformed both traditional and advanced algorithms, achieving 3-50x higher compression ratios than traditional algorithms, surpassing the second-best algorithm by up to 30%. Simulation experiments verified that SolarZip can reduce data transmission time by up to 270x while ensuring the preservation of scientific usability. Conclusions. The SolarZip framework significantly enhances solar observational data compression efficiency, while preserving scientific usability by dynamically selecting the optimal compression methods based on observational scenarios and user requirements. This approach offers a promising data management solution for deep space missions, such as Solar Orbiter.
关键词	methods: data analysis space vehicles: instruments techniques: image processing Sun: corona
DOI	10.1051/0004-6361/202555193
收录类别	SCI
语种	英语
资助项目	Belgian Federal Science Policy Office (BELPSO) ; Centre National d'Etudes Spatiales (CNES) ; UK Space Agency (UKSA) ; Bundesministerium fur Wirtschaft und Energie (BMWi) through the Deutsches Zentrum fuer Luft- und Raumfahrt (DLR) ; Swiss Space Office (SSO)[62032023] ; Swiss Space Office (SSO)[T2125013] ; National Natural Science Foundation of China[E461050] ; Innovation Funding of ICT, CAS[042274216] ; NSFC Fund[50 OT 2304] ; German Space Agency (DLR)
WOS研究方向	Astronomy & Astrophysics
WOS类目	Astronomy & Astrophysics
WOS记录号	WOS:001596517000008
出版者	EDP SCIENCES S A
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41629
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Tao, Dingwen
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Elect Sci & Technol China, Chengdu 610054, Peoples R China 3.Leibniz Inst Astrophys Potsdam AIP, Sternwarte 16, Potsdam 14482, Germany 4.Univ Potsdam, Inst Phys & Astron, Karl Liebknecht Str 24-25, D-14476 Potsdam, Germany 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 6.Minzu Univ China, Beijing 100081, Peoples R China 7.Chinese Acad Sci, Yunnan Observ, Kunming 650216, Peoples R China 8.Chinese Acad Sci, Ctr Astron Mega Sci, Beijing 100012, Peoples R China
推荐引用方式 GB/T 7714	Liu, Zedong,Tan, Song,Warmuth, Alexander,et al. SolarZip: An efficient and adaptive compression framework for Solar EUV imaging data: Application to Solar Orbiter/EUI data[J]. ASTRONOMY & ASTROPHYSICS,2025,702:17.
APA	Liu, Zedong.,Tan, Song.,Warmuth, Alexander.,Schuller, Frederic.,Hong, Yun.,...&Tao, Dingwen.(2025).SolarZip: An efficient and adaptive compression framework for Solar EUV imaging data: Application to Solar Orbiter/EUI data.ASTRONOMY & ASTROPHYSICS,702,17.
MLA	Liu, Zedong,et al."SolarZip: An efficient and adaptive compression framework for Solar EUV imaging data: Application to Solar Orbiter/EUI data".ASTRONOMY & ASTROPHYSICS 702(2025):17.