为提高自适应光学系统中Hartmann-Shack波前传感器的动态测量范围和测量精度, 对由CCD采集的波前光斑图进行了质心探测研究。介绍了波前传感器的工作原理, 根据127单元传感器的结构特征和实际人眼光斑图的畸变特点, 提出了一种动态定位光斑区域、动态分割区域内部阈值以及锁定最优探测窗口的自适应光斑质心探测方法。讨论了该方法中阈值等级选取对人眼光斑图质心探测的影响, 并通过仿真和实验分析了算法的质心探测精度和算法对噪声影响的鲁棒性。实验结果表明, 光斑区域内选取阈值等级为总等级数的(50±3)%时最合适; 与其他方法相比, 自适应质心探测方法的探测误差减小了60%以上; 将该探测方法运用至自适应光学视网膜成像系统的波前传感器中, 可将人眼像差RMS值从0.728λ闭环校正到0.081λ(λ=785 nm), 达到衍射极限, 并获得视网膜图像。本方法针对光斑特征选择不同实验参数, 弥补了传统算法的局限性, 基本满足了人眼像差测量的可行性和实用性。

In order to improve the dynamic measurement range and measurement accuracy of the Hartmann-Shack Wavefront Sensor (HSWS) in an adaptive optics system, the centroid detection for a wavefront spot pattern collected by a CCD is researched. The principle of HSWS is introduced and an adaptive centroid detection method by dynamic positioning spot region, dynamic segmenting threshold level and locking optimal detection window is presented according to the structure features of HSWS with 127 units and the distortion characteristics of actual human eye spot pattern.The effects of threshold level selection on human eye spot centriod detection are discussed and the centroid detection accuracy and noise robustness of the method are analyzed through simulation and experiments. Experimental results indicate that selecting the threshold level to be (50±3)% of the total grade amount is more appropriate and the centroid detection error can be decreased by 60% or more as compared with that of other detection methods. By using adaptive centroid detection method in the HSWS of an adaptive optical retina imaging system, human eye aberration can be reduced from 0.728λ to 0.081λ in RMS(λ=785 nm) through a closed loop correction.Moreover, the system can reach the diffraction limit basically and can obtain a retina image. These results show that the adaptive centroid detection method can select different experimental parameters aimed at the characteristics of spots, which makes up the limitations of the general methods.It meets the feasibility and practicability of human eye aberration measurement.