点光源哈特曼最优阈值估计方法研究

发布时间：2018-05-24 10:10

本文选题：夏克-哈特曼波前传感器 + 高斯光斑　；参考：《物理学报》2017年09期

【摘要】：针对夏克-哈特曼波前传感器探测系统中噪声随时间及空间变化频率较快的特点,为了准确估计系统的最优阈值,根据高斯光斑与噪声的分布特性,提出一种以滑动窗口内像素均值及图像信号的局部梯度作为参数,构造关于噪声权重函数的方法,由此获得子孔径阈值的最优估计值,并详细分析了算法的基本原理和实现过程.以典型处理方法获取的阈值与理论最优阈值的误差作为评价标准,仿真和实验结果表明本文提出的阈值估计方法在不同信噪比、不同光斑大小的条件下,均能取得优于典型阈值处理方法获得的结果,且与理论最优阈值的误差小于10%.
[Abstract]:In order to estimate the optimal threshold of the system, according to the distribution characteristics of Gao Si spot and noise, in order to estimate the optimal threshold of the system accurately, aiming at the characteristics of fast frequency variation of noise with time and space in the detection system of Shack-Hartmann wavefront sensor, In this paper, a method of constructing the noise weight function using the pixel mean in the sliding window and the local gradient of the image signal as parameters is proposed, and the optimal estimation of the subaperture threshold is obtained. The basic principle and implementation process of the algorithm are analyzed in detail. The error between the threshold obtained by the typical processing method and the theoretical optimal threshold is taken as the evaluation criterion. The simulation and experimental results show that the proposed threshold estimation method is based on different SNR and different spot sizes. The results obtained are better than those obtained by the typical threshold processing method, and the error from the theoretical optimal threshold is less than 10%.
【作者单位】：中国科学院自适应光学重点实验室;中国科学院光电技术研究所;中国科学院大学;
【分类号】：TP391.41;TP212

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