Model-based network architecture for image reconstruction in lensless imaging

Author(s):  
Tianjiao Zeng ◽  
Edmund Y. Lam
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Changyan Zhu ◽  
Eng Aik Chan ◽  
You Wang ◽  
Weina Peng ◽  
Ruixiang Guo ◽  
...  

AbstractMultimode fibers (MMFs) have the potential to carry complex images for endoscopy and related applications, but decoding the complex speckle patterns produced by mode-mixing and modal dispersion in MMFs is a serious challenge. Several groups have recently shown that convolutional neural networks (CNNs) can be trained to perform high-fidelity MMF image reconstruction. We find that a considerably simpler neural network architecture, the single hidden layer dense neural network, performs at least as well as previously-used CNNs in terms of image reconstruction fidelity, and is superior in terms of training time and computing resources required. The trained networks can accurately reconstruct MMF images collected over a week after the cessation of the training set, with the dense network performing as well as the CNN over the entire period.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 155039-155046
Author(s):  
Faguang Wang ◽  
Yue Wang ◽  
Hongmei Wang ◽  
Chaogang Tang

2015 ◽  
Vol 26 (10) ◽  
pp. 105401 ◽  
Author(s):  
Haiteng Wu ◽  
Jian Chen ◽  
Shiwei Wu ◽  
Haoran Jin ◽  
Keji Yang

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