Shim Seong-O
Department of Computer and Network Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia.
Microsc Res Tech. 2022 Mar;85(3):940-947. doi: 10.1002/jemt.23963. Epub 2021 Oct 19.
Shape from focus (SFF) is a technique to recover the shape of an object from multiple images taken at various focus settings. Most of conventional SFF techniques compute focus value of a pixel by applying one of focus measure operators on neighboring pixels on the same image frame. However, in the optics with limited depth of field, neighboring pixels of an image have different degree of focus for curved objects, thus the computed focus value does not reflect the accurate focus level of the pixel. Ideally, an accurate focus value of a pixel needs to be measured from the neighboring pixels lying on tangential plane of the pixel in image space. In this article, a tangential plane on each pixel location (i, j) in image sensor is searched by selecting one of five candidate planes based on the assumption that the maximum variance of focus values along the optical axis is achieved from the neighborhood lying on tangential plane of the pixel (i, j). Then, a focus measure operator is applied on neighboring pixels lying on the searched plane. The experimental results on both the synthetic and real microscopic objects show the proposed method produces more accurate three-dimensional shape in comparison to conventional SFF method that applies focus measures on original image planes.
聚焦形状（SFF）是一种从在不同聚焦设置下拍摄的多幅图像中恢复物体形状的技术。大多数传统的SFF技术通过对同一图像帧上的相邻像素应用一种聚焦度量算子来计算像素的聚焦值。然而，在景深有限的光学系统中，对于弯曲物体，图像的相邻像素具有不同程度的聚焦，因此计算出的聚焦值不能反映像素的准确聚焦水平。理想情况下，像素的准确聚焦值需要从图像空间中位于该像素切平面上的相邻像素进行测量。在本文中，基于沿着光轴的聚焦值的最大方差是从位于像素（i，j）切平面上的邻域获得的这一假设，通过从五个候选平面中选择一个来搜索图像传感器中每个像素位置（i，j）处的切平面。然后，将聚焦度量算子应用于在搜索到的平面上的相邻像素。对合成和真实微观物体的实验结果表明，与在原始图像平面上应用聚焦度量的传统SFF方法相比，该方法能产生更准确的三维形状。
