光子学报, 2020, 49 (2): 0201003, 网络出版: 2020-03-19
基于多通道盲识别的自适应光学图像事后处理 下载: 540次
Post Processing for Adaptive Optics Imaging Based on Multi-channel Blind Recognition
自适应光学 图像处理 多通道盲识别 点扩散函数 互质性 Adaptive optics Image processing Multi-channel blind recognition Point spread function Mutual quality
摘要
为实时恢复天文或空间目标的湍流退化成像,提出一种适应大气湍流动态变化的多通道自适应光学图像恢复方法.以自适应光学校正后不同时刻的目标成像作为多个通道,建立求解系统点扩散函数的线性方程,根据解出的点扩散函数利用超拉普拉斯算法,求解待观测目标的估计值.结果表明:不同时刻的点扩散函数之间存在互质关系,满足多通道盲识别的理论要求.利用建立的线性方程求解出的点扩散函数与原点扩散函数的均方误差在10-30~10-27量级,采用超拉普拉斯算法恢复出的目标成像与原始目标之间的均方误差在10-5~10-4量级.本文研究为湍流退化图像的实时恢复提供了理论基础.
Abstract
In order to restore turbulence-degraded imaging of astronomical or space targets in real time, this paper proposes the multi-channel blind recognition method, which can be applied to the dynamic changes of atmospheric turbulence. Target imaging at different time after adaptive optical correction are regarded as multiple channels to establish the point spread function of system. The super-Laplace algorithm is used to solve the target after obtaining estimations of point spread function. Results show that there exists a mutual relationship between point spread functions at different moments, which satisfies the theory of multi-channel blind recognition. The Mean Square Error(MSE) between the solved point spread function and the original point spread function is in the order of 10-30~10-27 and the MSE between the recovered target image and the original target is in the order of 10-5~10-4. Research results provide a theoretical basis for real-time restoration of turbulence-degraded images.
李鑫, 吴阳, 方舟, 徐奇, 杨海波, 杨慧珍. 基于多通道盲识别的自适应光学图像事后处理[J]. 光子学报, 2020, 49(2): 0201003. Xin LI, Yang WU, Zhou FANG, Qi XU, Hai-bo YANG, Hui-zhen YANG. Post Processing for Adaptive Optics Imaging Based on Multi-channel Blind Recognition[J]. ACTA PHOTONICA SINICA, 2020, 49(2): 0201003.