With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …

Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …

Deep learning-based image reconstruction methods have achieved remarkable success in
phase recovery and holographic imaging. However, the generalization of their image …

Phase unwrapping is an indispensable step for many optical imaging and metrology
techniques. The rapid development of deep learning has brought ideas to phase …

Recent years have witnessed the unprecedented progress of deep learning applications in
digital holography (DH). Nevertheless, there remain huge potentials in how deep learning …

Imaging through scattering media is one of the hotspots in the optical field, and impressive
results have been demonstrated via deep learning (DL). However, most of the DL …

Lensless imaging eliminates the need for geometric isomorphism between a scene and an
image while allowing the construction of compact, lightweight imaging systems. However, a …

Tomographic flow cytometry by digital holography is an emerging imaging modality capable
of collecting multiple views of moving and rotating cells with the aim of recovering their …

In this Letter, for the first time, to the best of our knowledge, we propose a digital holographic
reconstruction method with a one-to-two deep learning framework (Y-Net). Perfectly fitting …

This roadmap article focuses on spatially incoherent digital holography (IDH).
Representative IDH methods such as optical scanning holography (OSH), Fresnel …