Horisaki Ryoichi, Nishizaki Yohei, Kitaguchi Katsuhisa, Saito Mamoru, Tanida Jun
Appl Opt. 2021 Feb 1;60(4):A323-A328. doi: 10.1364/AO.404151.
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.