| Literature DB >> 33690416 |
Ryoichi Horisaki, Yohei Nishizaki, Katsuhisa Kitaguchi, Mamoru Saito, Jun Tanida.
Abstract
In this paper, we present a noniterative method for 3D computer-generated holography based on deep learning. A convolutional neural network is adapted for directly generating a hologram to reproduce a 3D intensity pattern in a given class. We experimentally demonstrated the proposed method with optical reproductions of multiple layers based on phase-only Fourier holography. Our method is noniterative, but it achieves a reproduction quality comparable with that of iterative methods for a given class.Year: 2021 PMID: 33690416 DOI: 10.1364/AO.404151
Source DB: PubMed Journal: Appl Opt ISSN: 1559-128X Impact factor: 1.980