Zhao Yu, Erdenebat Munkh-Uchral, Alam Md-Shahinur, Piao Mei-Lan, Jeon Seok-Hee, Kim Nam
Appl Opt. 2019 Feb 10;58(5):A242-A250. doi: 10.1364/AO.58.00A242.
Recently, computer-generated holograms (CGHs) of real three-dimensional (3D) objects have become widely used to support holographic displays. Here, a multiple-camera holographic system featuring an efficient depth grid is developed to provide the correct depth cue. Multidepth cameras are used to acquire depth and color information from real scenes, and then to virtually reconstruct point cloud models. Arranging the depth cameras in an inward-facing configuration allowed simultaneous capture of objects from different directions, facilitating rendering of the entire surface. The multiple relocated point cloud gridding method is proposed to generate efficient depth grids by classifying groups of object points with the same depth values in the red, green, and blue channels. CGHs are obtained by applying a fast Fourier transform diffraction calculation to the grids. Full-color reconstructed images were obtained flexibly and efficiently. The utility of our method was confirmed both numerically and optically.
最近，真实三维（3D）物体的计算机生成全息图（CGH）已被广泛用于支持全息显示。在此，开发了一种具有高效深度网格的多相机全息系统，以提供正确的深度线索。多深度相机用于从真实场景中获取深度和颜色信息，然后虚拟重建点云模型。将深度相机以向内配置排列，可以同时从不同方向捕获物体，便于对整个表面进行渲染。提出了多重重定位点云网格化方法，通过对红色、绿色和蓝色通道中具有相同深度值的物体点组进行分类来生成高效的深度网格。通过对网格应用快速傅里叶变换衍射计算来获得CGH。灵活高效地获得了全彩重建图像。我们方法的实用性在数值和光学上都得到了证实。
