We propose a holographic image restoration method using an autoencoder, which is an artificial neural network. Because holographic reconstructed images are often contaminated by direct light, conjugate light, and speckle noise, the discrimination of reconstructed images may be difficult. In this paper, we demonstrate the restoration of reconstructed images from holograms that record page data in holographic memory and QR codes by using the proposed method.
@article{arxiv.1612.03959,
title = {Autoencoder-based holographic image restoration},
author = {Tomoyoshi Shimobaba and Yutaka Endo and Ryuji Hirayama and Yuki Nagahama and Takayuki Takahashi and Takashi Nishitsuji and Takashi Kakue and Atsushi Shiraki and Naoki Takada and Nobuyuki Masuda and Tomoyoshi Ito},
journal= {arXiv preprint arXiv:1612.03959},
year = {2017}
}