Reconstruction of Ligaments and Droplets Via Multiview Digital Inline Holography

Abstract

Abstract Digital inline holography (DIH) is a three-dimensional (3D) measurement technique widely used in the characterizations of particles, droplets, and bubbly flows. When collimated coherent light passes an object field, the disturbed and undisturbed components will superimpose at the imaging plane and form an interference pattern (hologram) due to their phase variation. By analyzing the phase information encoded in the hologram, the shapes and locations of objects can be reconstructed. However, the reconstruction produces higher levels of uncertainty along the line of sight, which is the out-of-plane direction normal to the imaging plane. Additionally, the reconstructions algorithm cannot resolve structures blocked by other features along the recording path. To overcome these limitations, prior works have implemented DIH from two to three views on simple geometries. In this work, multiview digital inline holography is presented with (≥3) views to enable the reconstruction of 3D structures with complex surface topologies, including ligaments and droplets during the primary liquid breakup. The approach is similar to DIH but with a different postprocessing method that combines the information on 3D edge outlines extracted from different DIH viewing angles. Two reconstruction approaches, an outline-based method, and another cross section-based method, are developed and applied on holograms of a 3D-printed test model imitating droplet breakup. With only three views, both methods provide limited reconstruction results with various artifacts. The outline-based method uses more spatial information but, due to practical limitations, results in lower-fidelity reconstructions than the cross section-based method. In general, DIH reconstructions struggle with concave structures even with more than six views due to shadowing of obstructed structures. However, when the number of views increases to six, the cross section-based reconstruction method yields morphological details close to the test model.