Deep-learning-generated holography

Ryoichi Horisaki; Ryosuke Takagi; Jun Tanida

doi:10.1364/ao.57.003859

Deep-learning-generated holography

Ryoichi Horisaki (The University of Osaka) iD Ryosuke Takagi (The University of Osaka) Jun Tanida (The University of Osaka) iD

Journal: Applied Optics • 2018-05-07 • Optica Publishing Group • ISSN: 0003-6935

Abstract

We present a method for computer-generated holography based on deep learning. The inverse process of light propagation is regressed with a number of computationally generated speckle data sets. This method enables noniterative calculation of computer-generated holograms (CGHs). The proposed method was experimentally verified with a phase-only CGH.

Subjects & Keywords

# Advanced Optical Imaging Technologies # Engineering # Digital Holography and Microscopy # Physics and Astronomy # Optical measurement and interference techniques # Computer Science

How to Cite this Article

                    Ryoichi Horisaki, Ryosuke Takagi, Jun Tanida (2018). "Deep-learning-generated holography". Applied Optics. https://doi.org/10.1364/ao.57.003859                

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Identifiers & Provenance

DOI: https://doi.org/10.1364/ao.57.003859 ↗
PMID: 29791353 ↗
OpenAlex: W2800651752 ↗
Primary Index: OPENALEX