Depth-layer weighted prediction method for a full-color polygon-based holographic system with real objects

We propose a full-color polygon-based holographic system for real three-dimensional (3D) objects using a depth-layer weighted prediction method. The proposed system is composed of four main stages: acquisition, preprocessing, hologram generation, and reconstruction. In the preprocessing stage, the point cloud model is separated into red, green, and blue channels with depth-layer weighted prediction. The color component values are characterized based on the depth information of the real object, then color prediction is derived from the measurement data. The computer-generated holograms reconstruct 3D full-color images with a strong sensation of depth resulting from the polygon approach. The feasibility of the proposed method was confirmed by numerical and optical reconstruction.