Fast and accurate autofocus control using Gaussian standard deviation and gradient-based binning
Fast and accurate autofocus control using Gaussian standard deviation and gradient-based binning
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DOI：
10.1364/oe.425118
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发表时间：
2021-06-21
期刊：
影响因子：
3.8
通讯作者：
Du, Xian
中科院分区：
文献类型：
--
作者：
DiMeo, Peter;Sun, Lu;Du, Xian
我们提出了一个快速和准确的自动对焦算法，使用高斯标准差和基于梯度的分箱。该算法不使用优化过程迭代搜索最佳焦点，而是直接计算高斯形状的焦点测量（FM）曲线的平均值以找到最佳焦点位置，并使用FM曲线标准偏差来适应运动步长。计算仅需要3-4张散焦图像来确定FM曲线的中心位置。此外，通过基于FM曲线标准偏差分配运动步长，根据离焦度量自适应地控制运动步长的大小，从而避免过冲和不需要的图像处理。我们的实验验证了所提出的方法比最先进的自适应爬山（AHC）的速度更快，并提供了令人满意的精度测量的均方根误差。与AHC方法相比，所提出的方法需要减少80%的图像用于聚焦。此外，由于这种显着减少图像处理，所提出的方法减少了22%的AHC方法相比，autofbcus完成时间。所提出的方法在良好照明和低照明条件下观察到类似的性能。(C)2021年美国光学学会根据OSA开放获取出版协议的条款
We propose a fast and accurate autofbcus algorithm using Gaussian standard deviation and gradient-based binning. Rather than iteratively searching for the optimal focus using an optimization process, the proposed algorithm directly calculates the mean of the Gaussian shaped focus measure (FM) curve to find the optimal focus location and uses the FM curve standard deviation to adapt the motion step size. The calculation only requires 3-4 defocused images to identify the center location of the FM curve. Furthermore, by assigning motion step sizes based on the FM curve standard deviation, the magnitude of the motion step is adaptively controlled according to the defocused measure, thus avoiding overshoot and unneeded image processing. Our experiment verified the proposed method is faster than the state-of-the-art Adaptive Hill-Climbing (AHC) and offers satisfactory accuracy as measured by root-mean-square error. The proposed method requires 80% fewer images for focusing compared to the AHC method. Moreover, due to this significant reduction in image processing, the proposed method reduces autofbcus time to completion by 22% compared to the AHC method. Similar performance of the proposed method was observed in both well-lit and low-lighting conditions. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement