Yong Liu, Dingfa Huang, Yong Jiang
School of Civil Engineering, Southwest Jiaotong University, Cheng Du, China.
Appl Opt. 2012 Jul 20;51(21):4945-53. doi: 10.1364/AO.51.004945.
Temporal phase unwrapping is an important method for shape measurement in structured light projection. Its measurement errors mainly come from both the camera noise and nonlinearity. Analysis found that least-squares fitting cannot completely eliminate nonlinear errors, though it can significantly reduce the random errors. To further reduce the measurement errors of current temporal phase unwrapping algorithms, in this paper, we proposed a phase averaging method (PAM) in which an additional fringe sequence at the highest fringe density is employed in the process of data processing and the phase offset of each set of the four frames is carefully chosen according to the period of the phase nonlinear errors, based on fast classical temporal phase unwrapping algorithms. This method can decrease both the random errors and the systematic errors with statistical averaging. In addition, the length of the additional fringe sequence can be changed flexibly according to the precision of the measurement. Theoretical analysis and simulation experiment results showed the validity of the proposed method.
时间相位展开是结构光投影中形状测量的一种重要方法。其测量误差主要来自相机噪声和非线性。分析发现，最小二乘拟合虽能显著降低随机误差，但不能完全消除非线性误差。为进一步降低当前时间相位展开算法的测量误差，本文基于快速经典时间相位展开算法，提出了一种相位平均方法（PAM），即在数据处理过程中采用一组最高条纹密度的附加条纹序列，并根据相位非线性误差的周期精心选择每组四帧的相位偏移。该方法通过统计平均可同时降低随机误差和系统误差。此外，附加条纹序列的长度可根据测量精度灵活改变。理论分析和仿真实验结果验证了该方法的有效性。
