华南理工大学学报(自然科学版) ›› 2022, Vol. 50 ›› Issue (4): 90-99.doi: 10.12141/j.issn.1000-565X.210348

所属专题: 2022年电子、通信与自动控制

• 电子、通信与自动控制 • 上一篇    下一篇

基于高阶强度传输方程改进的相位物体层析重建算法

程鸿张晓龙刘勇朱啸天4   

  1. 安徽大学
  • 收稿日期:2021-05-27 修回日期:2021-09-02 出版日期:2022-04-25 发布日期:2021-09-24
  • 通信作者: 程鸿 (1981-),女,博士,副教授,主要从事计算机视觉、光学成像和信号处理研究 E-mail:chenghong@ ahu. edu. cn
  • 作者简介:程鸿 (1981-),女,博士,副教授,主要从事计算机视觉、光学成像和信号处理研究
  • 基金资助:
    安徽省高等学校自然科学研究项目;安徽省自然科学基金

An Improved Tomographic Reconstruction of Phase Objects Based on High-order Transport of Intensity Equation

CHENG Hong1 ZHANG Xiaolong2 LIU Yong3 ZHU Xiaotian4   

  • Received:2021-05-27 Revised:2021-09-02 Online:2022-04-25 Published:2021-09-24
  • Contact: 程鸿 (1981-),女,博士,副教授,主要从事计算机视觉、光学成像和信号处理研究 E-mail:chenghong@ ahu. edu. cn
  • About author:程鸿 (1981-),女,博士,副教授,主要从事计算机视觉、光学成像和信号处理研究

摘要: 经典的层析成像方法通常只考虑物体的强度重建,往往丢失了相位,但是相位包含了物体表面的深度、形状、折射率等信息,相比于强度而言更为重要。强度传输方程作为一种经典的相位恢复算法,能够直接获从已知的强度中计算出相位。本文提出了一种能够层析重建物体相位信息的新算法,该算法在高阶强度传输方程的基础上改进以获得更高精度的相位结果,再经过滤波反投影重建物体的三维相位信息。在反投影重建过程中加入了旋转中心校正的步骤使重建结果更为精确,实验结果表明,该算法在解决由于强度微分近似约束造成的相位精度低问题的同时,可以获得高精度的物体三维相位重建结果。

关键词: 层析成像, 高阶强度传输方程, 多平面迭代, 相位恢复, 强度微分

Abstract: Classical tomography method usually only considers the intensity reconstruction of the object, and often loses the phase, but the phase contains the information of the depth, shape, refractive index and so on of the surface of the object, which is more important than the intensity. As a classical phase retrieval algorithm,the Transport of Intensity Equation can directly calculate the phase from the known intensity. In this paper, a new algorithm can reconstruct the phase information of objects by tomography.The proposed algorithm is improved based on the high-order Transport of Intensity Equation to obtain higher precision phase results, and then reconstruct the three - dimensional phase information of the object through filtered back projection. Adding rotation center correction steps to the back projection reconstruction process makes the results more accurate. The experimental results show that the algorithm can obtain high precision three-dimensional phase reconstruction results while solving the low phase accuracy caused by intensity differential approximation constraints.

Key words: Tomography, High-order Transport of Intensity Equation, Multi-plane iteration, Phase retrieval, Intensity differential

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