Yin Xiaoming, Li Xiang, Zhao Liping, Fang Zhongping
Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore, Singapore 638075.
Appl Opt. 2009 Nov 10;48(32):6088-98. doi: 10.1364/AO.48.006088.
A Shack-Hartmann wavefront sensor (SWHS) splits the incident wavefront into many subsections and transfers the distorted wavefront detection into the centroid measurement. The accuracy of the centroid measurement determines the accuracy of the SWHS. Many methods have been presented to improve the accuracy of the wavefront centroid measurement. However, most of these methods are discussed from the point of view of optics, based on the assumption that the spot intensity of the SHWS has a Gaussian distribution, which is not applicable to the digital SHWS. In this paper, we present a centroid measurement algorithm based on the adaptive thresholding and dynamic windowing method by utilizing image processing techniques for practical application of the digital SHWS in surface profile measurement. The method can detect the centroid of each focal spot precisely and robustly by eliminating the influence of various noises, such as diffraction of the digital SHWS, unevenness and instability of the light source, as well as deviation between the centroid of the focal spot and the center of the detection area. The experimental results demonstrate that the algorithm has better precision, repeatability, and stability compared with other commonly used centroid methods, such as the statistical averaging, thresholding, and windowing algorithms.
夏克-哈特曼波前传感器（SWHS）将入射波前分割成许多子部分，并将波前畸变检测转化为质心测量。质心测量的精度决定了夏克-哈特曼波前传感器的精度。已经提出了许多方法来提高波前质心测量的精度。然而，这些方法大多是从光学角度进行讨论的，基于夏克-哈特曼波前传感器光斑强度具有高斯分布的假设，而这不适用于数字夏克-哈特曼波前传感器。在本文中，我们提出了一种基于自适应阈值和动态窗口方法的质心测量算法，通过利用图像处理技术将数字夏克-哈特曼波前传感器应用于表面轮廓测量的实际应用中。该方法可以通过消除各种噪声的影响，如数字夏克-哈特曼波前传感器的衍射、光源的不均匀性和不稳定性以及光斑质心与检测区域中心之间的偏差，精确且稳健地检测每个焦斑的质心。实验结果表明，与其他常用的质心方法，如统计平均、阈值化和窗口化算法相比，该算法具有更好的精度、重复性和稳定性。
