计算机科学
图像质量
光学
分辨率(逻辑)
职位(财务)
图像分辨率
计算机视觉
极限(数学)
人工智能
图像(数学)
算法
物理
数学
财务
数学分析
经济
作者
Mingtao Shang,Zhen‐Li Huang,Yujie Wang
出处
期刊:Applied Optics
[The Optical Society]
日期:2022-04-21
卷期号:61 (13): 3516-3516
被引量:2
摘要
Super-resolution localization microscopy (SRLM) breaks the diffraction limit successfully and improves the resolution of optical imaging systems by nearly an order of magnitude. However, SRLM typically takes several minutes or longer to collect a sufficient number of image frames that are required for reconstructing a final super-resolution image. During this long image acquisition period, system drift should be tightly controlled to ensure the imaging quality; thus, several drift correction methods have been developed. However, it is still unclear whether the performance of these methods is able to ensure sufficient image quality in SRLM. Without a clear answer to this question, it is hard to choose a suitable drift correction method for a specific SRLM experiment. In this paper, we use both theoretical analysis and simulation to investigate the relationship among drift correction precision, localization precision, and position estimation precision. We propose a concept of relative localization precision for evaluating the effect of drift correction on imaging resolution, which would help to select an appropriate drift correction method for a specific experiment.
科研通智能强力驱动
Strongly Powered by AbleSci AI