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Markov random field based phase demodulation of interferometric images

机译:基于马尔可夫随机场的干涉图像相位解调

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摘要

We present a novel method to solve the sign ambiguity for phase demodulation from a single interferometric image that possibly contains closed fringes. The problem is formulated in a Markov random field (MRF) energy minimization framework with the assumption of phase gradient orientation continuity. The binary pairwise objective function is non-submodular and therefore its minimization is an NP-hard problem, for which we devise a multigrid hierarchy of quadratic pseudoboolean optimization problems that can be improved iteratively to approximate the optimal solution. We name the method MSARI algorithm, for Markov based sign ambiguity resolution in interferometry. Compared with traditional path-following phase demodulation methods, the new approach does not require any heuristic scanning strategy, is not subject to the propagation of error, and the extension to three dimensional fringe patterns is straightforward. A set of experiments with synthetic data and real prelens tear film interferometric images of the human eye demonstrate the effectiveness and robustness of the proposed algorithm as compared with existing state-of-the-art phase demodulation methods.
机译:我们提出了一种新颖的方法来解决从可能包含闭合条纹的单个干涉仪图像进行相位解调的符号模糊性。该问题在马尔可夫随机场(MRF)能量最小化框架中提出,并假设相位梯度方向连续性。二进制成对目标函数是非子模的,因此其最小化是一个NP难题,为此,我们设计了二次伪布尔优化问题的多重网格层次结构,可以对其进行迭代改进,以逼近最佳解。我们将方法MSARI算法命名为干涉测量中基于Markov的符号模糊度解决方案。与传统的路径跟踪相位解调方法相比,该新方法不需要任何启发式扫描策略,并且不受误差传播的影响,并且可以很容易地扩展到三维条纹图案。一组使用合成数据和人眼真实的前镜头泪膜干涉图像进行的实验证明,与现有的最新相位解调方法相比,该算法的有效性和鲁棒性。

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