Research on convolutional neural network to realize high-quality dynamic holographic display

Abstract

There are still some challenges in the computation speed and reproduction quality of holographic display. In this paper, a method is proposed to realize a high-quality 3D holographic display by using a complex value convolutional neural network. Firstly, the layer-based method is used to cut and layer the object. The amplitude and phase of each layer of the object are calculated by a complex value network at the same time. Then, the output of the complex value type of the network is converted into a phase-only hologram, and each layer of the hologram is superimposed to reproduce the complete 3D object. In addition, a novel color convolutional neural network is used to generate R, G and B three-color holograms simultaneously, reducing the time required for three-channel recalculation of holograms. The proposed method only takes 16 ms to generate a hologram from single-layer object, the average peak signal-to-noise ratio of the reconstructed image is 28 dB, and the structural similarity exceeds 0.99, which realizes a high-quality dynamic holographic display. The experimental results confirm the feasibility of the proposed method and provide a new method for real-time holographic display of 3D object.