Author Affiliations
Abstract
Biophotonics Laboratory, University of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China
We propose a resolution enhancement method for a lensless in-line holographic microscope (LIHM) by combining the hologram segmentation and pixel super-resolution (PSR) techniques. Our method is suitable for imaging specific target objects in samples, where the in-line hologram is disturbed by other objects in the samples. The resolution-enhancement capability of our method was proved by numerical simulations and imaging experiments while using a standard resolution target in a two-layer setup. We also applied our LIHM system to image the sample of living algae Euglena gracilis in water solution for further demonstration.
090.1995 Digital holography 170.3880 Medical and biological imaging Chinese Optics Letters
2019, 17(11): 110901
天津大学精密仪器与光电子工程学院光电信息技术教育部重点实验室, 天津 300072
条纹中心提取是线结构光表面形貌测量的关键问题，提出一种基于主成分分析方法实现结构光条纹中心提取的方法。利用大津阈值法提取图像的感兴趣区域(ROI)，在经两次高斯卷积得到条纹的梯度分布的基础上确定条纹中心的初始位置，利用主成分分析来确定这些点上法线方向；以初始位置为基准点，对条纹的灰度分布函数在法线方向进行二阶泰勒展开求得条纹中心的精确位置。实验结果表明，该算法具有速度快、精度高等特点，相对Steger算法，均方误差(MSE)小于0.003 pixel，速度提高了近3 倍。该方法能够实现结构光条纹中心线的快速高精度提取，为结构光视觉检测的实时应用奠定了基础。
测量 形貌检测 线结构光 中心提取 主成分分析
