Affiliation:
1. Hubei Key Laboratory of Intelligent Robot
Abstract
The miniaturized imaging spectrometers face bottlenecks in reconstructing the high-resolution spectral image. In this study, we have proposed an optoelectronic hybrid neural network based on zinc oxide (ZnO) nematic liquid crystal (LC) microlens array (MLA). This architecture optimizes the parameters of the neural network by constructing the TV-L1-L2 objective function and using mean square error as a loss function, giving full play to the advantages of ZnO LC MLA. It adopts the ZnO LC-MLA as optical convolution to reduce the volume of the network. Experimental results show that the proposed architecture has reconstructed a 1536 × 1536 pixels resolution enhancement hyperspectral image in the wavelength range of [400 nm, 700 nm] in a relatively short time, and the spectral accuracy of reconstruction has reached just 1 nm.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hubei Province
Knowledge Innovation Program of Wuhan-Basic Research
New Generation Information Technology Innovation Project of China Ministry of Education
Hubei Provincial Key Laboratory of Intelligent Robot
The Engineering Research Center of Digital Imaging and Display, Ministry of Education, Soochow University
Wuhan Institute of Technology
Subject
Atomic and Molecular Physics, and Optics
Cited by
2 articles.
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