Zhao Yu, Kwon Ki-Chul, Erdenebat Munkh-Uchral, Jeon Seok-Hee, Piao Mei-Lan, Kim Nam
Opt Express. 2019 Oct 14;27(21):29746-29758. doi: 10.1364/OE.27.029746.
A multiple-camera holographic system using non-uniformly sampled 2D images and compressed point cloud gridding (C-PCG) is suggested. High-quality, digital single-lens reflex cameras are used to acquire the depth and color information from real scenes; these are then virtually reconstructed by the uniform point cloud using a non-uniform sampling method. The C-PCG 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. Holograms are obtained by applying fast Fourier transform diffraction calculations to the grids. Compared to wave-front recording plane methods, the quality of the reconstructed images is substantially better, and the computational complexity is dramatically reduced. The feasibility of our method is confirmed both numerically and optically.
提出了一种使用非均匀采样二维图像和压缩点云网格化（C-PCG）的多相机全息系统。使用高质量的数码单反相机从真实场景中获取深度和颜色信息；然后使用非均匀采样方法通过均匀点云对这些信息进行虚拟重建。提出了C-PCG方法，通过对红、绿、蓝通道中具有相同深度值的物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全息图。与波前记录平面方法相比，重建图像的质量显著提高，计算复杂度大幅降低。我们方法的可行性在数值和光学上均得到了证实。
