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作 者:Li-Yue Tong Jia-Ben Lin Yuan-Yong Deng Kai-Fan Ji Jun-Feng Hou Quan Wang Xiao Yang
机构地区:[1]National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100101,China [2]Key Laboratory of Solar Activity and Space Weather,National Space Science Center,Chinese Academy of Sciences,Beijing 100190,China [3]School of Astronomy and Space Science,University of Chinese Academy of Sciences,Beijing 100049,China [4]Yunnan Observatories,Chinese Academy of Sciences,Kunming 650216,China
出 处:《Research in Astronomy and Astrophysics》2024年第4期214-221,共8页天文和天体物理学研究(英文版)
基 金:supported by the National Key R&D Program of China(grant No.2022YFF0503800);by the National Natural Science Foundation of China(NSFC)(grant No.11427901);by the Strategic Priority Research Program of the Chinese Academy of Sciences(CAS-SPP)(grant No.XDA15320102);by the Youth Innovation Promotion Association(CAS No.2022057)。
摘 要:The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.
关 键 词:methods:data analysis techniques:image processing Sun:magnetic fields Sun:photosphere
分 类 号:TN9[电子电信—信息与通信工程]
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