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.

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