Zheng Shanshan, Liao Meihua, Wang Fei, He Wenqi, Peng Xiang, Situ Guohai
Opt Express. 2021 Nov 22;29(24):40091-40105. doi: 10.1364/OE.443127.
Non-line-of-sight (NLOS) imaging has received considerable attentions for its ability to recover occluded objects from an indirect view. Various NLOS imaging techniques have been demonstrated recently. Here, we propose a white-light NLOS imaging method that is equipped only with an ordinary camera, and not necessary to operate under active coherent illumination as in other existing NLOS systems. The central idea is to incorporate speckle correlation-based model into a deep neural network (DNN), and form a two-step DNN strategy that endeavors to learn the optimization of the scattered pattern autocorrelation and object image reconstruction, respectively. Optical experiments are carried out to demonstrate the proposed method.
非视距（NLOS）成像因其能够从间接视角恢复被遮挡物体的能力而受到了广泛关注。最近已经展示了各种非视距成像技术。在此，我们提出一种白光非视距成像方法，该方法仅配备普通相机，无需像其他现有非视距系统那样在有源相干照明下运行。其核心思想是将基于散斑相关性的模型纳入深度神经网络（DNN），并形成一种两步DNN策略，分别致力于学习散射图案自相关的优化和物体图像重建。进行了光学实验以验证所提出的方法。
