Yatabe Kohei, Ishikawa Kenji, Oikawa Yasuhiro
J Opt Soc Am A Opt Image Sci Vis. 2017 Jan 1;34(1):87-96. doi: 10.1364/JOSAA.34.000087.
This paper presents a non-iterative phase retrieval method from randomly phase-shifted fringe images. By combining the hyperaccurate least squares ellipse fitting method with the subspace method (usually called the principal component analysis), a fast and accurate phase retrieval algorithm is realized. The proposed method is simple, flexible, and accurate. It can be easily coded without iteration, initial guess, or tuning parameter. Its flexibility comes from the fact that totally random phase-shifting steps and any number of fringe images greater than two are acceptable without any specific treatment. Finally, it is accurate because the hyperaccurate least squares method and the modified subspace method enable phase retrieval with a small error as shown by the simulations. A MATLAB code, which is used in the experimental section, is provided within the paper to demonstrate its simplicity and easiness.
本文提出了一种从随机相移条纹图像中进行非迭代相位恢复的方法。通过将超精确最小二乘椭圆拟合方法与子空间方法（通常称为主成分分析）相结合，实现了一种快速准确的相位恢复算法。所提出的方法简单、灵活且准确。它无需迭代、初始猜测或调整参数即可轻松编码。其灵活性源于这样一个事实，即完全随机的相移步长以及任意数量大于两幅的条纹图像无需任何特殊处理都是可接受的。最后，它之所以准确是因为超精确最小二乘方法和改进的子空间方法能够实现误差较小的相位恢复，如仿真所示。本文还提供了用于实验部分的MATLAB代码，以证明其简单性和易用性。
