Zhang Haoyu, Cao Jie, Zhou Dong, Cui Huan, Cheng Yang, Hao Qun
Opt Express. 2022 Oct 10;30(21):39152-39161. doi: 10.1364/OE.472889.
Computational ghost imaging (CGI) using stereo vision is able to achieve three-dimensional (3D) imaging by using multiple projection units or multiple bucket detectors which are separated spatially. We present a compact 3D CGI system that consists of Risley prisms, a stationary projection unit and a bucket detector. By rotating double prisms to various angles, speckle patterns appear to be projected by a dynamic virtual projection unit at different positions and multi-view ghost images are obtained for 3D imaging. In the process of reconstruction, a convolutional neural network (CNN) for super-resolution (SR) is adopted to enhance the angular resolution of reconstructed images. Moreover, an optimized 3D CNN is implemented for disparity estimation and 3D reconstruction. The experimental results validate the effectiveness of the method and indicate that the compact system with flexibility has potential in applications such as navigation and detection.
利用立体视觉的计算鬼成像（CGI）能够通过使用多个空间分离的投影单元或多个桶探测器来实现三维（3D）成像。我们提出了一种紧凑的3D CGI系统，该系统由里斯利棱镜、一个固定投影单元和一个桶探测器组成。通过将双棱镜旋转到不同角度，动态虚拟投影单元似乎在不同位置投射散斑图案，并获得用于3D成像的多视角鬼图像。在重建过程中，采用用于超分辨率（SR）的卷积神经网络（CNN）来提高重建图像的角分辨率。此外，还实现了一种优化的3D CNN用于视差估计和3D重建。实验结果验证了该方法的有效性，并表明具有灵活性的紧凑系统在导航和检测等应用中具有潜力。
