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

TL;DR

This paper introduces a large-scale 3D particle imaging method using a beam propagation model that significantly improves accuracy and efficiency over existing techniques, enabling detailed reconstructions from a single hologram.

Contribution

The authors develop a novel beam propagation-based algorithm for holographic 3D particle imaging that enhances accuracy and reduces computation time compared to prior methods.

Findings

Up to 9× higher accuracy than single-scattering models.

Reduces computation time by two orders of magnitude.

Outperforms existing methods in deep and dense particle fields.

Abstract

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$\times$ 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 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.