Quantum mechanics

Holographic display

Phase (matter)

Process (computing)

Net (polyhedron)

Holography

Operating system

Iterative reconstruction

Computer science

Physics

Digital holography

Mathematics

Optics

Artificial intelligence

Geometry

Deep learning

Digital holographic microscopy

Optics Letters

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 the holographic reconstruction process, the Y-Net can simultaneously reconstruct intensity and phase information from a single digital hologram. As a result, this compact network with reduced parameters brings higher performance than typical network variants. The experimental results of the mouse phagocytes demonstrate the advantages of the proposed Y-Net.

Y-Net: a one-to-two deep learning framework for digital holographic reconstruction