Abstract
A multiple sub-holograms optimization method for holographic near-eye display (NED) based on holographic viewing-window (HVW) is proposed. The HVW is a hologram generated by the point source method (PSM) with the spatial frequency constraint, and the complete reconstructed images can be observed through it. In this paper, the HVW is a phase-only hologram (POH) of a three dimensional (3D) multiplane image and it is split into multiple sub-holograms that are optimized simultaneously for pupil movement by the convolutional neural network (CNN), where each optimized constant phase (OCP) is added to the wavefront of corresponding point source. Both the simulation and the experimental results show that the quality of the reconstructed image corresponding to each sub-hologram has significantly improved, especially compared with the random constant phase (RCP) method. Moreover, we establish a holographic NED system with a 4f system to pan the optimized POH to the pupil plane to generate the HVW, and then a camera with an additional aperture is used to capture the reconstructed images corresponding to each sub-hologram. In this paper, the high-quality 3D multiplane images with natural motion parallax can be observed through an 8.64 mm×8.64 mm HVW with nine sub-holograms.
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