4.6 Article

Y-Net: a one-to-two deep learning framework for digital holographic reconstruction

Journal

OPTICS LETTERS
Volume 44, Issue 19, Pages 4765-4768

Publisher

Optica Publishing Group
DOI: 10.1364/OL.44.004765

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Funding

  1. National Natural Science Foundation of China (NSFC) [61927810]
  2. NSAF Joint Fund [U1730137]
  3. Fundamental Research Funds for the Central Universities [3102019ghxm018]

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In this Letter, for the first time, to the best of our knowledge, we propose a digital holographic reconstruction method with a one-to-two deep learning framework (Y-Net). Perfectly fitting the holographic reconstruction process, the Y-Net can simultaneously reconstruct intensity and phase information from a single digital hologram. As a result, this compact network with reduced parameters brings higher performance than typical network variants. The experimental results of the mouse phagocytes demonstrate the advantages of the proposed Y-Net. (C) 2019 Optical Society of America

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