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.
© 2021 Optical Society of America
Full Article | PDF ArticleMore Like This
Ryoichi Horisaki, Ryosuke Takagi, and Jun Tanida
Appl. Opt. 57(14) 3859-3863 (2018)
David Blinder, Takashi Nishitsuji, and Peter Schelkens
Opt. Express 31(2) 3072-3082 (2023)
Ji-Won Kang, Byung-Seo Park, Jin-Kyum Kim, Dong-Wook Kim, and Young-Ho Seo
Appl. Opt. 60(24) 7391-7399 (2021)