Image Reconstruction of Multimode Fiber Scattering Media Based on Deep Learning

被引：0
|
作者：
Meng L. [1 ]
Hu H. [1 ,2 ]
Hu J. [1 ]
Bu S. [1 ]
Gao H. [1 ]
机构：
[1] College of Information Science and Engineering, Northeastern University, Shenyang
[2] School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai
来源：
Meng, Lu (menglu@ise.neu.edu.cn) | 1600年 / Science Press卷 / 47期
关键词：
Deep learning; Dense connection; DenseUnet; Fiber optics; Image processing; Image reconstruction; Multimode fiber;
D O I：
10.3788/CJL202047.1206005
中图分类号：
学科分类号：
摘要：
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. © 2020, Chinese Lasers Press. All right reserved.
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