论文标题
时间多头神经全息图：具有快速重量的空间光调节器的全息近眼显示器的灵活框架
Time-multiplexed Neural Holography: A flexible framework for holographic near-eye displays with fast heavily-quantized spatial light modulators
论文作者
论文摘要
全息近眼显示器为虚拟和增强现实系统（包括感知重要的焦点提示）提供了前所未有的功能。尽管人工智能 - 用于计算机生成全息图（CGH）的驱动算法最近在提高全息图的图像质量和合成效率方面取得了长足的进步，但这些算法并不直接适用于新兴的相位空间光调节器（SLM），但具有非常快速的相位，但具有非常有限的相位控制。这些SLM的速度提供了时间的多路复用功能，从本质上则可以启用部分共同的全息显示模式。在这里，我们报告了这些类型的全息近眼显示器的相机校准的波传播模型的进步，我们开发了一个CGH框架，可稳健地优化快速SLMS的大量量化相位模式。我们的框架可以灵活地支持运行时监督不同类型的内容，包括2D和2.5D RGBD图像，3D焦点堆栈和4D Light Fields。使用我们的框架，我们在模拟和实验中展示了所有这些情况的最新结果。
Holographic near-eye displays offer unprecedented capabilities for virtual and augmented reality systems, including perceptually important focus cues. Although artificial intelligence--driven algorithms for computer-generated holography (CGH) have recently made much progress in improving the image quality and synthesis efficiency of holograms, these algorithms are not directly applicable to emerging phase-only spatial light modulators (SLM) that are extremely fast but offer phase control with very limited precision. The speed of these SLMs offers time multiplexing capabilities, essentially enabling partially-coherent holographic display modes. Here we report advances in camera-calibrated wave propagation models for these types of holographic near-eye displays and we develop a CGH framework that robustly optimizes the heavily quantized phase patterns of fast SLMs. Our framework is flexible in supporting runtime supervision with different types of content, including 2D and 2.5D RGBD images, 3D focal stacks, and 4D light fields. Using our framework, we demonstrate state-of-the-art results for all of these scenarios in simulation and experiment.
