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中文摘要：
为提高自适应光学（AO）图像的空间分辨率,提出一种基于帧选择和极大似然估计的AO图像多帧联合去卷积算法.该算法基于极大似然估计,根据图像的高斯噪声模型建立多帧AO图像的联合对数似然函数.首先对观测的多帧AO图像进行帧选择,遴选高质量的降质图像;然后结合观测条件和AO系统特性,推导点扩散函数估计模型;最后建立迭代求解公式,得到多帧AO图像联合去卷积方法.实验结果表明,与基于期望值最大化的Richardson-Lucy算法（Richardson-Lucy EM算法）和基于合并惩罚函数的自适应应图像复原算法（CPF-Adaptive算法）相比,该算法的峰值信噪比分别提高9%和5%,Laplace梯度模分别提高11%和8%,且得到了较清晰的目标图像.
英文摘要：
In order to improve the spatial resolution of adaptive optics（AO）images,we proposed multi-frame joint deconvolution algorithm for AO images based on frame-selection and maximum likelihood estimation.The algorithm took maximum likelihood estimation as the basic principle.According to the Gaussian noise model of the image,the joint log likelihood function of multi-frame AO images was established.Firstly,we selected frames of the observed multi-AO images and selected the high quality degraded images.Secondly,combined with the observed conditions and characteristics of AO system,the estimation model of point spread function was derived.Finally,we established iterative solution formulas,and obtained multi-frame AO images joint deconvolution method.Theexperimental results show that,compared with the Richardson-Lucy EM or CPF-Adaptive algorithm,the PSNR values of the proposed algorithm are increased by 9% and 5% respectively,and the Laplacian gradient moduli are increased by 11% and 8% respectively,and clearer target images are obtained.
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