Markman Adam, Shen Xin, Javidi Bahram
Opt Lett. 2017 Aug 15;42(16):3068-3071. doi: 10.1364/OL.42.003068.
Conventional two-dimensional (2D) imaging systems that operate in the visible spectrum may perform poorly in environments under low light illumination. In this work, we present the potential of passive three-dimensional (3D) integral imaging (II) to perform 3D imaging of a scene under low light conditions in the visible spectrum and without the need for a photon counting or cooled CCD camera. Using dedicated algorithms, we demonstrate that the reconstructed 3D integral image is naturally optimum in a maximum likelihood sense in low light levels and in the presence of detector noise enabling object visualization in the scene. The conventional 2D imaging fails due to the limited number of photons. Using 3D imaging, we demonstrate the potential for 3D detection of objects behind occlusion in a photon-starved scene. To the best of our knowledge, this is the first report of experimentally using II sensing under low illumination conditions for 3D visualization and 3D object detection in the presence of obscurations with a conventional image sensor.
工作在可见光谱范围内的传统二维（2D）成像系统在低光照环境下可能表现不佳。在这项工作中，我们展示了被动三维（3D）积分成像（II）在可见光谱范围内的低光照条件下对场景进行3D成像的潜力，且无需光子计数或制冷电荷耦合器件（CCD）相机。通过使用专用算法，我们证明了重建的3D积分图像在低光照水平和存在探测器噪声的情况下，在最大似然意义上自然是最优的，从而能够实现场景中物体的可视化。由于光子数量有限，传统的2D成像会失败。通过使用3D成像，我们展示了在光子匮乏的场景中对遮挡物后面的物体进行3D检测 的潜力。据我们所知，这是首次报道在低光照条件下使用积分成像传感技术，通过传统图像传感器在存在遮挡物的情况下进行3D可视化和3D物体检测。
