Opt Express. 2023 Feb 27;31(5):7643-7658. doi: 10.1364/OE.482498.
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.
微型成像光谱仪在重建高分辨率光谱图像方面面临瓶颈。在这项研究中，我们提出了一种基于氧化锌（ZnO）向列液晶（LC）微透镜阵列（MLA）的光电混合神经网络。该架构通过构建 TV-L1-L2 目标函数并使用均方误差作为损失函数来优化神经网络的参数，充分发挥 ZnO LC MLA 的优势。它采用 ZnO LC-MLA 作为光学卷积来减小网络的体积。实验结果表明，所提出的架构在相对较短的时间内重建了一个分辨率增强的 1536×1536 像素高光谱图像，其重建的光谱精度达到了 1nm。
