Chen Liming, Ding Rachel, Zhang Song
Appl Opt. 2024 Apr 20;63(12):3219-3227. doi: 10.1364/AO.517997.
This paper presents an adaptive focus stacking method for large depth-of-field (DOF) 3D microscopic structured-light imaging systems. Conventional focus stacking methods typically capture images under a series of pre-defined focus settings without considering the attributes of the measured object. Therefore, it is inefficient since some of the focus settings might be redundant. To address this problem, we first employ the focal sweep technique to reconstruct an initial rough 3D shape of the measured objects. Then, we leverage the initial 3D data to determine effective focus settings that focus the camera on the valid areas of the measured objects. Finally, we reconstruct a high-quality 3D point cloud using fringe images obtained from these effective focus settings by focus stacking. Experimental results demonstrate the success of the proposed method.
本文提出了一种适用于大景深三维微观结构光成像系统的自适应聚焦堆叠方法。传统的聚焦堆叠方法通常在一系列预定义的聚焦设置下采集图像，而不考虑被测物体的属性。因此，由于某些聚焦设置可能是多余的，该方法效率较低。为了解决这个问题，我们首先采用焦扫技术重建被测物体的初始粗糙三维形状。然后，利用初始三维数据确定有效的聚焦设置，将相机聚焦在被测物体的有效区域上。最后，通过聚焦堆叠，利用从这些有效聚焦设置中获得的条纹图像重建高质量的三维点云。实验结果证明了该方法的有效性。
