压缩感知框架下的太阳图像重建方法

Research on the solar image reconstruction method based on compressive sensing

研制对日成像天线阵的主要困难体现在有限的预算和天线数目之间的矛盾,如何减少天线数目即降低采样率是重要目标之一.鉴于压缩感知理论能够以远低于奈奎斯特采样定律要求的数据恢复出原始信号和太阳图像的稀疏性,提出了基于压缩感知框架的太阳图像重建方法.通过仿真太阳图像和实际天文图像的成像实验例证了方案的有效性,表明在天线阵天线元数目和阵型确定的情况下,该方案在对相邻点源的分辨能力、对展源的保形能力以及动态范围方面有较优的性能.

One of the important goals of the developing antenna array of solar imaging is how to decrease the cell number of the array,due to the contradiction between limited budget and massive antennas.Inspired by the ability of compressed sensing to recover exactly the original signal from highly sub-Nyquist-rate samples and the sparse characters of solar image,this paper proposes a solar image reconstruction method based on the compressive sensing theory.The effectiveness of this scheme is illustrated by experiments of both simulated solar image and real astronomical image.Results show superiority of the proposed method in the resolution of the adjacent point source,the shape maintenance of the extanded source and the dynamic range.