吉林大学学报（理学版）2017，Vol.55Issue(5)：1199-1206,8.DOI:10.13413/j.cnki.jdxblxb.2017.05.30
基于帧选择和极大似然估计的自适应光学图像多帧联合去卷积算法
Multi-frame Joint Deconvolution Algorithm for Adaptive Optics Images Based on Frame-Selection and Maximum Likelihood Estimation
摘要
Abstract
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.The experimental 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.关键词
图像复原/极大似然估计/自适应光学(AO)/点扩散函数/帧选择技术Key words
image restoration/maximum likelihood estimation/adaptive optics (AO)/point spread function (PSF)/frame-selection technology分类
信息技术与安全科学引用本文复制引用
张丽娟,李东明,杨进华,邱欢,刘颖,刘欢..基于帧选择和极大似然估计的自适应光学图像多帧联合去卷积算法[J].吉林大学学报（理学版）,2017,55(5):1199-1206,8.基金项目
国家自然科学基金(批准号:61402193)、吉林省教育厅项目(批准号:JJKH20170575KJ)和国家大学生创新训练项目(批准号:201610193048). （批准号:61402193）
