基于统计逼近的Stoilov算法光栅参数优化设计

Design of Stoilov Algorithm Grating Parameter Optimization Based on Statistical Approach

基于Stoilov算法的相位测量轮廓术(PMP)三维测量过程中,由于其表达式中四种奇异现象的存在,致使用Stoilov算法时出现解相错误,所以不能很好地重构三维物体。采用统计逼近的方法补偿Stoilov算法表达式中出现的异常点,弥补了Stoilov算法的缺陷。同时Stoilov算法对光栅周期及条纹对比度比较敏感,当光强变化较大时,相移图像对应的像素点发生突跳,影响测量精度。因此,提出一种基于统计逼近的Stoilov优化算法的光栅参数优化方法以提高测量精度。实验模拟不同的物体,发现存在重构三维物体时均方差最小的光栅周期和光栅条纹对比度,验证了光栅参数优化设计的可行性。

In the phase measuring profilometry （PMP） three-dimensional measurement based on Stoilov algorithm, the four abnormal phenomena lead to the incorrect phase calculation or incorrect phase unwrapping, so the measured object can′t be reconstructed well. The proposed method based on the statistical approach can restrain the abnormal phenomena availably and make up Stoilov algorithm defect. Meanwhile, it is found that Soilov algorithm is sensitive to the period and contrast of sinusoidal gratings. The pixel of phase imaging will be mutant and the measuring precision is to be influenced when the light intensity varies severely. Therefore, a method of grating parameter optimization based on the statistical approach Soilov algorithm is proposed. The measuring precision can be improved by optimizing the period and contrast of sinusoidal gratings under the experimental simulation. Experimental result shows its feasibility and validity.