Quality enhancement and GPU acceleration for a full-color holographic system using a relocated point cloud gridding method.

Abstract

The calculation of realistic full-color holographic displays is hindered by the high computational cost. Previously, we suggested a point cloud gridding (PCG) method to calculate monochrome holograms of real objects. In this research, a relocated point cloud gridding (R-PCG) method is proposed to enhance the reconstruction quality and accelerate the calculation speed in GPU for a full-color holographic system. We use a depth camera to acquire depth and color information from the real scene then reconstruct the point cloud model virtually. The R-PCG method allows us to classify groups of object points with the same depth values into grids in the red, green, and blue (RGB) channels. Computer-generated holograms (CGHs) are obtained by applying a fast Fourier transform (FFT) diffraction calculation to the grids. The feasibility of the R-PCG method is confirmed by numerical and optical reconstruction.