快照式光谱光场成像技术

针对快照式多维成像系统难以实现高维成像的问题,本文提出了一种快照式光谱光场成像方法,使用单个探测器实现了对目标场景光谱光场信息的快速获取。该方法将聚焦光场成像结构引入到快照式超光谱成像傅里叶变换光谱仪中,首先获取混叠了目标场景光场信息和干涉信息的原始图像,然后使用基于卷积神经网络的信息重建算法,将光场信息和干涉信息从原始图像中分别提取出来,并分别利用光场和干涉信息来重建目标场景的深度和光谱。本文搭建了快照式光谱光场成像系统,并对该系统在空间、光谱以及时间维度上的表现进行了实验验证。实验结果表明,该系统在将获取信息的维度扩展到七维的同时,其深度重建的均方根误差为7.7 mm,光谱重建的归一化均方根误差为6.87%。

Snapshot spectral light-field imaging technology

Realizing high-dimensional imaging for a snapshot multi-dimensional imaging system is difficult.Therefore,this study proposes a snapshot spectral light-field imaging method that can simultaneously record the light field and spectral information of a target scene using a single detector.This method introduces the paradigm of light-field imaging to Fourier transform imaging spectroscopy.A raw image composed of the light-field image and interference is then obtained.A convolutional neural network is developed to decouple the light-field image and interference.The depth and spectral information of the scene can then be reconstructed.The study also constructs a snapshot spectral-volumetric imaging system,and its performance in spatial,spectral,and temporal dimensions is verified through experiments.Experimental results showed that the root mean square error(RMSE)of depth reconstruction was 7.7 mm,and the normalized RMSE of spectral reconstruction was 6.87%when the acquired information was extended to seven dimensions.