混合搜索法在显微镜自动对焦中的应用

针对基于显微镜的自动对焦系统，本文提出了一种爬山搜索法和函数逼近法相结合的混合搜索算法。该算法中的爬山搜索法采用粗精结合的两段式算法。在粗略对焦时，大步距选用速度较快的灰度方差函数；当精细对焦时，小步距采用灵敏度较高的Laplacian函数；通过比较三幅图片来缩小对焦区间并且在该区间内采用函数逼近法来拟合出最佳对焦位置。该方法不仅大大减少了自动对焦所需要的图片数量，而且可以大幅度提高搜索精度。经实验验证，提出的新的搜索算法可以使搜索精度优于1 μm。

Applications of hybrid search strategy in microscope autofocus

For autofocus system of the microscope, this paper presents a hybrid search algorithm combining the mountain-climb search strategy with the approximation function strategy. In this algorithm, the mountain-climb search strategy adopts the two-stage algorithm of rough and fine focusing stage. In the rough focusing stage, the gray variance function is used to approach the focusing position quickly. In the fine focusing stage, the Laplacian function is used to locate the focusing position accurately. The algorithm narrows the focus interval by comparing three pictures and the approximation function strategy is used to fit the best focus in this range. This method greatly reduces the number of images required for autofocus and greatly improves the search accuracy. The experimental results indicate that this algorithm can make the search accuracy better than 1 μm.