Chinese Journal of Lasers, Volume. 47, Issue 12, 1206005(2020)

Image Reconstruction of Multimode Fiber Scattering Media Based on Deep Learning

Meng Lu1、*, Hu Haifeng1,2, Hu Jinzhou1, Bu Sihang1, and Gao Han1
Author Affiliations
  • 1College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China
  • 2School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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    Multimode fiber is a thick scattering medium. When the target image is projected onto the multimode optical fiber, multimode coupling will occur, thereby generating speckle images at the output of the fiber. In this work, multimode optical fiber imaging is restored based on deep learning, and the distortion of thick scattering media imaging is solved. DenseUnet is used and the speckle image is used as the input of the model for reconstructing the target image. The DenseUnet model employs a fusion mechanism to deepen the network depth, thus, improving the reconstruction accuracy and realizing good robustness. The experimental results reveal that DenseUnet can be used to reconstruct speckle images produced by multimode optical fibers with different lengths.

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    Meng Lu, Hu Haifeng, Hu Jinzhou, Bu Sihang, Gao Han. Image Reconstruction of Multimode Fiber Scattering Media Based on Deep Learning[J]. Chinese Journal of Lasers, 2020, 47(12): 1206005

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    Paper Information

    Category: Fiber optics and optical communication

    Received: Jun. 22, 2020

    Accepted: --

    Published Online: Nov. 17, 2020

    The Author Email: Lu Meng (menglu@ise.neu.edu.cn)

    DOI:10.3788/CJL202047.1206005

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