Accelerating computation of CGH using convolutional symmetric compressed LUT method in 360° dynamic color 3D holographic display

In 360° color three-dimensional (3D) holographic display, numerous color computer-generated holograms (CCGH) are required to achieve compact distribution of view window on the viewing circumstance band [1]. However, traditional look-up-table methods cannot meet the needs of massive computing. This paper proposes a convolutional symmetric compressed look-up-table (CSC-LUT) method to accelerate CCGH computation based on the Fresnel diffraction theory and LUT. The proposed method can achieve one-time high-quality fast generation of CCGH by utilizing dynamic convolution operation, which is divided three processes. Firstly, the pre-calculated data of maximum horizontal modulation factor is compressed in 1D array by coordinate symmetry. Then, the test object is resampled to satisfy convolutional translation invariance. Finally, the dynamic convolution operation is used to simplify CCGH computation process rather than the point-by-point computation. Numerical simulation and optical experimental results show that our proposed method can achieve faster computation speed, higher reconstruction quality and wider application compared to conventional SC-LUT method. The further optimization method for parallel acceleration on the GPU framework can achieve real-time (>24fps) color holographic display corresponding to three perspectives of a 3D scene.