Hou Weihan, Wei Yangjie
Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, College of Computer Science and Engineering, Northeastern University, Wenhua Street 3, Shenyang 110819, China.
iScience. 2023 Sep 21;26(10):107976. doi: 10.1016/j.isci.2023.107976. eCollection 2023 Oct 20.
In the imaging process of conventional optical microscopy, the primary factor hindering microscope resolution is the energy diffusion of incident light, most directly described by the point spread function (PSF). Therefore, accurate calculation and measurement of PSF are essential for evaluating and enhancing imaging resolution. Currently, there are various methods to obtain PSFs, each with different advantages and disadvantages suitable for different scenarios. To provide a comprehensive analysis of PSF-obtaining methods, this study classifies them into four categories based on different acquisition principles and analyzes their advantages and disadvantages, starting from the propagation property of light in optical physics. Finally, two PSF-obtaining methods are proposed based on mathematical modeling and deep learning, demonstrating their effectiveness through experimental results. This study compares and analyzes these results, highlighting the practical applications of image deblurring.
在传统光学显微镜的成像过程中,阻碍显微镜分辨率的主要因素是入射光的能量扩散,最直接的描述是点扩散函数(PSF)。因此,准确计算和测量PSF对于评估和提高成像分辨率至关重要。目前,有多种获取PSF的方法,每种方法都有不同的优缺点,适用于不同的场景。为了对PSF获取方法进行全面分析,本研究从光学物理中光的传播特性出发,根据不同的采集原理将其分为四类,并分析了它们的优缺点。最后,基于数学建模和深度学习提出了两种获取PSF的方法,并通过实验结果证明了它们的有效性。本研究对这些结果进行了比较和分析,突出了图像去模糊的实际应用。