Literature DB >> 28463295

Autoencoder-based holographic image restoration.

Tomoyoshi Shimobaba, Yutaka Endo, Ryuji Hirayama, Yuki Nagahama, Takayuki Takahashi, Takashi Nishitsuji, Takashi Kakue, Atsushi Shiraki, Naoki Takada, Nobuyuki Masuda, Tomoyoshi Ito.   

Abstract

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 quick response codes by using the proposed method.

Year:  2017        PMID: 28463295     DOI: 10.1364/AO.56.000F27

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  1 in total

1.  Automatic Detection of Image-Based Features for Immunosuppressive Therapy Response Prediction in Oral Lichen Planus.

Authors:  Ziang Xu; Qi Han; Dan Yang; Yijun Li; Qianhui Shang; Jiaxin Liu; Weiqi Li; Hao Xu; Qianming Chen
Journal:  Front Immunol       Date:  2022-06-23       Impact factor: 8.786

  1 in total

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