Holographic near-eye displays are a promising technology to provide realistic and visually comfortable imagery with improved user experience, but their coherent light sources limit the image quality and restrict the types of patterns that can be generated. A partially-coherent mode, supported by emerging fast spatial light modulators (SLMs), has potential to overcome these limitations. However, these SLMs often have a limited phase control precision, which current computer-generated holography (CGH) techniques are not equipped to handle. In this work, we present a flexible CGH framework for fast, highly-quantized SLMs. This framework is capable of incorporating a wide range of content, including 2D and 2.5D RGBD images, 3D focal stacks, and 4D light fields, and we demonstrate its effectiveness through state-of-the-art simulation and experimental results.
Holographic near-eye displays have the potential to overcome many long-standing challenges for virtual and augmented reality (VR/AR) systems; they can reproduce full 3D depth cues, improve power efficiency, enable compact display systems, and correct for optical aberrations. Despite these remarkable benefits, this technology has been held back from widespread usage due to the limited image quality achieved by traditional holographic displays, the slow algorithms for computer-generated holography (CGH), and current bulky optical setups. Here, we review recent advances in CGH that utilize artificial intelligence (AI) techniques to solve these challenges.
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