Deep neural network-enabled resolution enhancement for the digital light field display based on holographic functional screen

The digital light-field display suffers from low resolution due to lack of planar pixels transformed into spatial information, which limits three-dimensional (3D) visual effect obviously. Herein, a pre-coding optimization of rendering the elemental image array (EIA) using a resolution-enhanced deep neural network (RE-DNN) is proposed, and it is used to enhance each reconstructed view perspective with high clarity besides using the holographic functional screen (HFS). The RE-DNN is used to cooperate with the HFS to form additional effective visual pixels/sub-pixels without increasement of physical planar resolution. The simulation and experimental presented 3D images with high clarity are demonstrated, verifying the feasibility and superiority of the proposed resolution enhancement method.