High-image-quality light field near-eye display with custom holographic functional screens and a pre-correction network

The light field near-eye display has been treated as an effective method to solve the vergence-accommodation conflict (VAC). Currently, it still suffers from critical bottlenecks, including low spatial resolution, discontinuous perception of elemental views, and severe aberrations. To overcome these challenges, a high-image-quality light field near-eye display is proposed, featuring a custom-designed holographic functional screen (HFS) and a deep-learning-based pre-correction network. The HFS is introduced to effectively increase the fill factor of the elemental views and seamlessly stitch the light field, thereby significantly enhancing the continuity and naturalness of the final image. Building upon this, the deep-learning network is further incorporated to suppress system aberrations, improving both imaging sharpness and detail fidelity. The efficacy of this method is validated through a prototype system that successfully achieves high-image-quality 3D reconstruction with a monocular diagonal field of view (FOV) of approximately 70°, an exit pupil diameter of 7 mm, and a wide depth range exceeding 3 diopters, substantially mitigating the aforementioned issues of discontinuity and aberrations. This research presents what we believe to be a novel and generalizable approach for developing high-performance light field near-eye displays.