Automatic centroid detection for Shack-Hartmann Wavefront sensor

Shark-Hartmann Wavefront sensor 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 Shack-Hartmann Wavefront Sensor. A lot of 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, and 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 have presented a new centroid measurement algorithm based on adaptive thresholding and dynamic windowing method by utilizing image processing techniques for practical application of the digital Shack-Hartmann Wavefront Sensor in surface profile measurement. The method can detect the centroid of the spot accurately and robustly by eliminating the influences of various noises such as diffraction of the digital SHWS, uneven and instability of the light source as well as deviation between the centroid of the spot and the center of the detection area. The experimental results demonstrate that the algorithm has better accuracy, repeatability and stability compared with other commonly used centroid methods such statistic averaging, thresholding and windowing algorithms.