Large-scale holographic particle 3D imaging with the beam propagation model

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 9x 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. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Automated summary

The novel algorithm developed is based on multiple-scattering beam propagation method combined with sparse regularization to reconstruct dense 3D particles of high refractive index contrast. A computationally efficient algorithm is devised to solve the inverse problem, significantly reducing the computation time and outperforming the single-scattering method in accuracy.