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通过结合主成分分析和最小二乘法从随机相移干涉图中提取相位

Phase extraction from randomly phase-shifted interferograms by combining principal component analysis and least squares method.

作者信息

Xu Jiancheng, Jin Weimin, Chai Liqun, Xu Qiao

机构信息

Institute of Information Optics, Zhejiang Normal University, Jinhua, Zhejiang 321004, China.

出版信息

Opt Express. 2011 Oct 10;19(21):20483-92. doi: 10.1364/OE.19.020483.

Abstract

A method combining the principal component analysis (PCA) and the least squares method (LSM) is proposed to extract the phase from interferograms with random phase shifts. The method estimates the initial phase by PCA, and then determines the correct global phase sign and reduces the residual phase error by LSM. Some factors that may influence the performance of the proposed method are analyzed and discussed, such as the number of frames used, the number of fringes in interferogram and the amplitude of random phase shifts. Numerical simulations and optical experiments are implemented to verify the effectiveness of this method. The proposed method is suitable for randomly phase-shifted interferograms.

摘要

提出了一种将主成分分析(PCA)和最小二乘法(LSM)相结合的方法,用于从具有随机相移的干涉图中提取相位。该方法通过主成分分析估计初始相位,然后通过最小二乘法确定正确的全局相位符号并减小残余相位误差。分析和讨论了一些可能影响所提方法性能的因素,如所用帧数、干涉图中的条纹数以及随机相移的幅度。进行了数值模拟和光学实验以验证该方法的有效性。所提方法适用于随机相移干涉图。

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