Zhang Hangying, Zhao Hong, Zhao Zixin, Zhuang Yiying, Fan Chen
Opt Express. 2019 Apr 15;27(8):10495-10508. doi: 10.1364/OE.27.010495.
Gram-Schmidt (GS) orthogonal normalization is a fast and efficient two-frame fringe phase demodulation method. However, the precision of the GS method is limited due to the residual background terms and noise, as well as several approximation operations in the GS method. To obtain a phase map with higher accuracy, we propose an algorithm combining GS orthogonal normalization and least squares iterative (LSI) phase shift algorithm (GS&LSI). In our method, the phase was first obtained using GS method, and then a refinement operation using LSI was adopted to get the final wrapped phase map. Because of the LSI process, the demodulation result is greatly improved in many cases. Simulation and experimental result are presented to validate the potential of the proposed method.
Gram-Schmidt(GS)正交归一化是一种快速高效的双帧条纹相位解调方法。然而,由于残余背景项和噪声以及GS方法中的若干近似运算,GS方法的精度受到限制。为了获得更高精度的相位图,我们提出了一种将GS正交归一化与最小二乘迭代(LSI)相移算法相结合的算法(GS&LSI)。在我们的方法中,首先使用GS方法获得相位,然后采用LSI进行细化操作以得到最终的包裹相位图。由于LSI过程,在许多情况下解调结果得到了极大改善。给出了仿真和实验结果以验证所提方法的潜力。