【摘要】 相位差法是常用的图像事后重建方法之一。为提高相位差法对太阳图像重建的鲁棒性，本文提出了基于低秩先验的改进的相位差法，即引入了图像核范数正则化到相位差模型中，并分别利用半二次分裂方法和BFGS求解图像子模型和相位子模型。在仿真退化的焦面和离焦面太阳图像上进行重建实验与分析，与基于Tikhonov正则化的经典相位差法相比，在无噪声和有噪声情况下基于低秩先验的相位差法在主观视觉效果和客观指标上均能够提高波前相位估计的精度，提高重建图像的质量。更多还原

【Abstract】 Phase diversity is one of the commonly used image post-reconstruction methods. In order to improve the robustness of phase diversity for solar image reconstruction, this paper proposes an improved phase diversity method based on the low-rank prior, i.e., the nuclear norm regularization of the image is introduced into the phase diversity model, and the image sub-model and the phase sub-model are solved by the half-quadratic splitting method and BFGS respectively. Reconstruction experiments and analysis are carried out on the simulated degraded focused and defocused solar images. Compared with the classical phase diversity based on Tikhonov regularization, the phase diversity based on low-rank prior can improve the accuracy of wavefront phase estimation and the quality of reconstructed images in terms of subjective visual effects and objective indexes in both the noisefree and noise-included cases.更多还原