基于分割缩放的欠采样相位图解包裹算法

为了提取所需的相位信息，克服噪声、断点以及欠采样等不利因素的影响，针对采样问题出现的根本原因（采样频率过低、图像条纹密度过高），在处理欠采样问题时采用基于分割缩放原理的相位解包裹算法，对密度过高的干涉条纹通过插值放大后再进行解包裹运算。在理论分析的基础上给出了具体的相位解包裹算法，模拟计算和实验验证都表明了该算法的可行性。结果表明，该算法对有欠采样相位的解包裹能取得不错的效果。

Unwrapping algorithm based on segmentation and zooming for undersampled wrapped phase

In order to obtain phase information, many unfavorable factors such as noise, breakpoint and under sampling must be overcome. Aimed at too low sampling frequency and high fringe density, the root cause of the undersampling problem, unwrapping algorithm based on segmentation and zooming principle was introduced. After enlarging interference fringe whose density is too high by interpolation method, the phase was unwrapped. The simulation and experimental results show the feasibility of the proposed algorithm. It turns out that it is an effective unwrapping algorithm for undersampled wrapped phase.