为了提高自适应光学（AO）图像的质量，研究了一种基于波前重构和自适应总变分（TV）的 AO图像复原方法。首先，基于 Zernike多项式进行波前重构，对点扩散函数（ PSF）进行初始估计。然后，提出了基于自适应总变分法的 AO图像复原的迭代求解，解决了联合去卷积问题。最后，通过图像复原实验验证本文算法的恢复效果。实验结果表明：与 RL-IBD算法和 FS-MLJD算法相比，本文算法的 NMSE值分别降低了 18.6%、10.7%，算法的 PSNR值分别提高了 4.47%、0.987%，算法的运算时间分别降低了 1.99%、13.66%。

In order to improve the image quality of adaptive optics (AO), an AO image restoration algorithm based on wavefront reconstruction and adaptive total variation (TV) is proposed in this work. First, wavefront reconstruction using the Zernike polynomial is employed for an initial estimate of the point spread function (PSF). Then, we developed our proposed iterative solutions based on the adaptive total variation for AO image restoration by addressing the joint deconvolution issue. Image restoration experiments were performed to verify the image restoration effect of our proposed algorithm. Compared with the RL-IBD and FS-MLJD algorithms, the experimental results show the normalized mean square error(NMSE) for a real AO image from our algorithm decreased by 18.6% and 10.7%, respectively, the peak signal-to-noise ratio(PSNR) increased by 4.47% and 0.987%, respectively, and the computation time decreased by 1.99% and 13.66%, respectively.