University of Massachusetts Boston, Department of Physics, Boston, Massachusetts, United States.
University of Massachusetts Boston, Department of Computer Science, Boston, Massachusetts, United States.
J Biomed Opt. 2024 Jul;29(7):076502. doi: 10.1117/1.JBO.29.7.076502. Epub 2024 Jul 13.
In in-line digital holographic microscopy (DHM), twin-image artifacts pose a significant challenge, and reduction or complete elimination is essential for object reconstruction.
To facilitate object reconstruction using a single hologram, significantly reduce inaccuracies, and avoid iterative processing, a digital holographic reconstruction algorithm called phase-support constraint on phase-only function (PCOF) is presented.
In-line DHM simulations and tabletop experiments employing the sliding-window approach are used to compute the arithmetic mean and variance of the phase values in the reconstructed image. A support constraint mask, through variance thresholding, effectively enabled twin-image artifacts.
Quantitative evaluations using metrics such as mean squared error, peak signal-to-noise ratio, and mean structural similarity index show PCOF's superior capability in eliminating twin-image artifacts and achieving high-fidelity reconstructions compared with conventional methods such as angular spectrum and iterative phase retrieval methods.
PCOF stands as a promising approach to in-line digital holographic reconstruction, offering a robust solution to mitigate twin-image artifacts and enhance the fidelity of reconstructed objects.
在在线数字全息显微镜（DHM）中，孪生像伪影是一个重大挑战，对于物体重建，减少或完全消除这些伪影至关重要。
为了使用单个全息图进行物体重建，显著减少误差，并避免迭代处理，提出了一种称为基于纯相位函数的相位支撑约束（PCOF）的数字全息重建算法。
采用滑动窗口方法进行在线 DHM 模拟和台式实验，以计算重建图像中相位值的算术平均值和方差。通过方差阈值处理，支撑约束掩模有效地消除了孪生像伪影。
使用均方误差、峰值信噪比和平均结构相似性指数等指标进行定量评估表明，与传统方法（如角谱和迭代相位恢复方法）相比，PCOF 在消除孪生像伪影和实现高保真重建方面具有优越的能力。
PCOF 是一种有前途的在线数字全息重建方法，为减轻孪生像伪影和提高重建物体的保真度提供了一种稳健的解决方案。
