Segmented Point Cloud Gridding Method for a Full-Color Holographic System With Real Objects - Zhao, Yu; Huang, Yuan; Zhu, Li-Ming; Bu, Jing-Wen; Du, Yu-Ren; Zhu, Ming-Yu; Zhu, Jin-Rong (Frontiers in Photonics, 2022)
The huge computing data of hologram calculation causes the heavy computational load for the realistic full-color holographic displays. In this paper, we proposed a segmented point cloud gridding (S-PCG) method to enhance the computing ability of a full-color holographic system. A depth camera is used to collect the color and depth information from actual scenes, and then these are reconstructed to the point cloud model. Object points are categorized into depth girds with identical depth values in the red, green, and blue (RGB) channels. In each channel, the depth girds are segmented into M × N parts, and only the effective area of the depth grids will be calculated. Computer-generated holograms (CGHs) are generated from efficient depth grids by using Fast Fourier transform (FFT). Compared to the wave-front recording plane (WRP) and traditional PCG methods, the computational complexity is dramatically reduced. The feasibility of the S-PCG approach is established through numerical and optical reconstruction.