Wang Hao, Tahir Waleed, Zhu Jiabei, Tian Lei
Opt Express. 2021 May 24;29(11):17159-17172. doi: 10.1364/OE.424752.
We develop a novel algorithm for large-scale holographic reconstruction of 3D particle fields. Our method is based on a multiple-scattering beam propagation method (BPM) combined with sparse regularization that enables recovering dense 3D particles of high refractive index contrast from a single hologram. We show that the BPM-computed hologram generates intensity statistics closely matching with the experimental measurements and provides up to 9× higher accuracy than the single-scattering model. To solve the inverse problem, we devise a computationally efficient algorithm, which reduces the computation time by two orders of magnitude as compared to the state-of-the-art multiple-scattering based technique. We demonstrate the superior reconstruction accuracy in both simulations and experiments under different scattering strengths. We show that the BPM reconstruction significantly outperforms the single-scattering method in particular for deep imaging depths and high particle densities.
我们开发了一种用于大规模三维粒子场全息重建的新型算法。我们的方法基于多重散射光束传播法(BPM)并结合稀疏正则化,能够从单个全息图中恢复具有高折射率对比度的密集三维粒子。我们表明,BPM计算全息图生成的强度统计与实验测量结果紧密匹配,并且比单散射模型的精度高9倍。为了解决逆问题,我们设计了一种计算效率高的算法,与基于多重散射的现有技术相比,该算法将计算时间减少了两个数量级。我们在不同散射强度下的模拟和实验中都证明了其卓越的重建精度。我们表明,BPM重建在特别是对于深度成像深度和高粒子密度的情况下,明显优于单散射方法。