剪切散斑干涉术中, 普遍采取相移法提取相位, 只可得到被包裹的相位信息, 进一步量化计算之前, 必须展开相位, 但是大量的散斑噪音使相位展开变得非常困难.本文提出基于图切割理论的相位展开算法, 将相位展开等价于整数的最优估计问题, 通过最小化能量函数展开相位, 无需对散斑包裹相位图进行滤波, 就可以从包含大量散斑噪音的包裹相位图中准确地提取出真实相位, 极大程度地保留了相位包裹图中的细节信息.对于同一幅模拟的散斑包裹相位图, 传统的质量导向枝切法和最小二乘法的均方根误差分别为11.707 6和4.977 5, 新算法的均方根误差则为0.945 9, 数值模拟与实验结果均验证了新算法优良的抗噪性能.

In electronic speckle pattern interferometry (ESPI), the true phase is generally extracted by the phasestepping method, which can only get the wrapped phase. Before the phase can be used to provide quantitative information, the wrapped phase must be unwrapped. But ESPI fringe patterns are contaminated with high levels of speckle noise, the task of phase unwrapping remains a challenge. In this article, a novel phase unwrapping algorithm based on graphcuts is proposed, which treats the phase unwrapping problem as integer optimizations. By the method of energy minimization, the novel algorithm can accurately extract the phase from wrapped phase images containing large amount of noise without prefiltering. For the same simulated wrapped speckle phase map,the RMSE(root mean squared error) of the traditional MaskCuts and LeastSquare are respectively 11.707 6 and 4.977 5, while the new algorithm's RMSE is 0.9459.Numerical simulation and experimental results both verify the excellent antinoise performance of the new algorithm.