共振扫描显微成像中的图像畸变校正

熊大曦; 刘云; 梁永; 娄艳阳; 郑贤良; 金鑫; 蒋克明; 黎海文; 李辉

doi:10.3788/OPE.20152310.2971

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共振扫描显微成像中的图像畸变校正

信息科学 | 更新时间：2020-08-13

- 共振扫描显微成像中的图像畸变校正
- Correction of distortion in microscopic imaging with resonant scanning
- 光学精密工程 2015年23卷第10期页码：2971-2979
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院大学北京,中国,100049
  3. 中国科学院苏州生物医学工程技术研究所江苏省医用光学重点实验室,江苏苏州,215163
- 作者简介：
- 基金信息：
  
  国家重大科学仪器设备开发专项资助项目(No.ZDYZ2013-1)();国家自然科学基金面上项目(No.61475185)();中科院BR计划资助项目()
- DOI：10.3788/OPE.20152310.2971
  中图分类号： TP391;TH742.9
- 收稿日期：2015-05-29，
  
  修回日期：2015-07-21，
  
  纸质出版日期：2015-10-25
- 稿件说明：
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熊大曦, 刘云, 梁永等. 共振扫描显微成像中的图像畸变校正[J]. 光学精密工程, 2015,23(10): 2971-2979

XIONG Da-xi, LIU Yun, LIANG Yong etc. Correction of distortion in microscopic imaging with resonant scanning[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10): 2971-2979
熊大曦, 刘云, 梁永等. 共振扫描显微成像中的图像畸变校正[J]. 光学精密工程, 2015,23(10): 2971-2979 DOI： 10.3788/OPE.20152310.2971.

XIONG Da-xi, LIU Yun, LIANG Yong etc. Correction of distortion in microscopic imaging with resonant scanning[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10): 2971-2979 DOI： 10.3788/OPE.20152310.2971.

摘要

设计了一种校正算法用于校正双光子荧光显微镜等高速扫描成像系统中共振振镜扫描导致的图像畸变。首先对共振振镜的扫描运动建立模型

推导出非线性扫描的运动公式

进而得到图像畸变公式;然后对一块朗奇光栅样品扫描成像

设计了多峰高斯拟合算法得到光栅所有条纹的宽度变化并通过最小二乘法将条纹宽度数据拟合成一条畸变曲线;最后利用畸变曲线对图像进行校正。结果表明:采用提出的校正算法可使系统最大畸变减小到传统正弦校正方法的1/3

相对畸变减小到1/5

校正效果比传统的正弦校正法提高了2倍。由于提出的曲线拟合校正算法不用增加额外的光路

且不需要切割边缘图像

故显示了极好的图像使用效率和校正效果。

Abstract

An efficient algorithm was proposed to correct the image distortion caused by a resonant scanner in higher speed scanning and imaging systems of confocal or two-photon laser scanning microscopes. A model of scanning movement for the resonant scanner was established

the movement formula of the nonlinear scanning was deduced

so that the distortion equation of the image was obtained. Then

a Ronchi grating sample was imaged by canning

the multi peak Gauss fitting algorithm was designed to get all grating line widths. Those unequal line-widths were fitted into a distortion curve by least square method. Finally

the image correction was achieved through compressing or streching original image based on correction coefficients from the distortion curve. Experimental results indicate that the curve fitting correction algorithm reduces the maximum distortion and the relative distortion to 1/3 and 1/5 those of traditional one and the correction effect is twice as much as that of sinusodal correction method. The fitting correction algorithm does not need to add other light paths and segment edge images

so it shows good image efficiency and correction effect.

关键词

Keywords

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