Research on Adaptive Optics Image Restoration Algorithm Based on Improved Joint Maximum a Posteriori Method

查看全文 作　　者：Lijuan [1]ZHANG;Yang [1]LI;Junnan [1]WANG;Ying [2]LIU 机构地区：[1]College of Computer Science and Engineering, Changchun University of Technology, Changchun, 130012, China;[2]School of Management Science and Informatton Engineering, Jilin University of Finance and Economics, Changchun, 130117, China 出　　处：《Photonic Sensors》索引2018年第8卷第1期,共7页 基　　金：This research is supported by the State Scholarship Fund of China (No. 201508220093), the National Science Foundation of China (No. 61402193), the Scientific and Technological Research Project of the Department of Education in Jilin Province (No. JJKH20170575KJ, and No. 2014142), and the Postdoctoral sustentation Fund of Jilin Province, the Department of Science and Technology of Jilin Province (No. 20160418080). 摘　　要：在这篇论文,我们建议一个点传播功能(PSF ) 重建方法和联合最大值为适应光学图象恢复的一个 posteriori (JMAP ) 评价方法。把 JMAP 方法用作基本原则,我们建立多框架的联合日志可能性的函数基于图象 Gaussian,噪音建模的适应光学(AO ) 图象。首先,联合观察条件和 AO 系统特征,为波前阶段效果的一个预言的 PSF 模型被开发;然后,我们基于我们的建议算法建立 AO 图象的反复的答案公式,探讨多框架 AO 图象关节 deconvolution 方法的实现过程。我们进行一系列实验在上模仿并且评估我们的建议算法的真实降级的 AO 图象。与维纳相比反复的盲目 deconvolution (Wiener-IBD ) 算法和 Richardson 露西 IBD 算法,我们的算法比其它包括更高的山峰 signal-to-noise 比率(PSNR ) 和拉普拉斯算符和(LS ) 价值有更好的恢复效果。研究结果为实际 AO 图象恢复有某个应用程序值。