光学-近红外太阳爆发探测仪（ONSET）运行以来，已经获得了大量太阳光球和色球的宝贵数据，对我国太阳物理学和空间天气学的发展做出了重要的贡献。但受限于技术储备，一直没有实现对观测图像质量的实时评价和选帧重建处理, 影响数据的后期使用。本项目拟在调研国内外天文望远镜尤其是太阳望远镜的图像处理相关技术基础上，系统研究并给出ONSET各波段的全日面和局部太阳图像的质量评价指标，进而研究ONSET图像数据的选帧和统计重建的最优方法，以期实现观测数据序列的挑选并重建出更高质量的观测图像数据，最终利用CPU+GPU技术实现基于上述方法的高速实时观测数据处理系统，提高ONSET图像数据的可用性，为后期科学分析提供更高质量的图像数据，促进ONSET在太阳物理研究和太阳爆发探测方面获得更多的科学产出。

Optical and NIR Solar Eruption Tracer(ONSET）has acquired a great number of solar chromosphere and photosphere data that contributes great to the research of the solar physics and space weather. But limited by the technical provisions, the acquired image data is not assessed and reconstructed in real-time which alleviates the following usage of the data. This project will investigate the image processing techniques commonly adopted by the domestic and international telescopes, especially the solar telescopes, research the features and the quality metrics of the images of the ONSET, research the statistical reconstruction technique, and develop a high-speed and real-time image processing and restoring system based on CPU+GPU for ONSET that may improve the processing speed and the data quality of the ONSET, and provide more reliable data for the research of the solar physics and eruptions.