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中国物理学会期刊

数字差分-积分快速相位解包裹算法研究

Fast phase unwrapping using digital differentiation-integration method

CSTR: 32037.14.aps.72.20230473
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  • 数字全息技术是目前应用最广泛的定量相位成像技术之一, 但是当测量相位较大的物体时, 需要解包裹算法才能计算出正确的相位信息. 目前, 已有的解包裹算法均面临计算量巨大、耗时的问题. 为了解决上述问题, 本文基于傅里叶变换相位恢复算法, 利用复振幅相位信息的完整性, 提出针对薄相位和连续大相位的基于数字差分-积分的快速直接解包裹算法. 该算法首先通过基本的傅里叶变换相位恢复算法操作后, 得到含有物体完整相位的复振幅信息; 随后, 从中提取两幅子复振幅信息, 并将二者相除, 再相位提取出其中信息, 便可得到一个物体真实相位差分信息; 最后, 沿差分方向对提取的相位差分信息进行积分, 便可得到解包裹后的相位信息. 同时通过仿真与具体实验对该算法进行了验证. 结果表明, 本文算法可以实现快速准确的解包裹相位直接恢复.

     

    Digital holography is one of the most widely used quantitative phase imaging technologies at present, owing to its non-contact, high-accuracy and full-filed measurement. However, when the optical path difference induced by the measurement sample is larger than the used wavelength, a phase unwrapping algorithm has to be utilized to unwrap the phase and retrieve the actual phase. And the existing phase unwrapping algorithms suffer huge computational burden and slow retrieval speed. Although they have been greatly improved, their retrieval speed is limited by the phase unwrapping. In order to solve the above-mentioned problems, a digital differentiation-integration based phase unwrapping is proposed in this paper. This algorithm is based on the fact that the actual phase information is contained in the complex-valued function after Fourier transform, band-pass filter and inverse Fourier transform. After Fourier transform, band-pass filter and inverse Fourier transform, a complex-valued function containing the actual phase is retrieved, and two sub complex-valued functions can be extracted with just one-pixel shift digitally. Then, two functions are divided pixel by pixel, and another complex-valued function containing the differentiation of the actual phase is obtained. So the differential phase can be retrieved easily by the phase extraction. Finally, the retrieved differential phase is integrated along the inverse direction of shifting, and the unwrapped phase can be obtained directly. This algorithm can work effectively when the variation of the measurement phase is in a range of (–π, π. This algorithm is just based on the Fourier transform and the complex-valued division. Unlike the existing unwrapping algorithms, this algorithm is much easier to conduct and has light computation burden. Therefore, this algorithm can realize fast and accurate phase reconstruction directly. Several simulation and experimental results can verify the effectiveness of this algorithm.

     

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