Display performance optimization method for light field displays based on a neural network

Abstract

Crosstalk between adjacent views, lens aberrations, and low spatial resolution in light field displays limit the quality of 3D images. In the present study, we introduce a display performance optimization method for light field displays based on a neural network. The method pre-corrects the encoded image from a global perspective, which means that the encoded image is pre-corrected according to the light field display results. The display performance optimization network consists of two parts: the encoded image pre-correction network and the display network. The former realizes the pre-correction of the original encoded image (OEI), while the latter completes the modeling of the display unit and realizes the generation from the encoded image to the viewpoint images (VIs). The pre-corrected encoded image (PEI) obtained through the pre-correction network can reconstruct 3D images with higher quality. The VIs are accessible through the display network. Experimental results suggest that the proposed method can reduce the graininess of 3D images significantly without increasing the complexity of the system. It is promising for light field displays since it can provide improved 3D display performance.