Learned Hardware-in-the-loop Phase Retrieval for Holographic Near-Eye Displays
Learned Hardware-in-the-loop Phase Retrieval for Holographic Near-Eye Displays
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DOI：
10.1145/3414685.3417846
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发表时间：
2020-12-01
影响因子：
6.2
通讯作者：
Heide, Felix
中科院分区：
文献类型：
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作者：
Chakravarthula, Praneeth;Tseng, Ethan;Heide, Felix
全息术可以说是最有前途的技术，可以为增强现实和虚拟现实提供宽视场紧凑型眼镜式近眼显示器。然而，现有全息显示器的图像质量与当前一代传统显示器的图像质量相去甚远，这实际上使得当今的全息显示系统不切实际。这种差距主要源于真实全息显示器中用于计算全息图的“未知”光传输模型的理想化近似值的严重偏差。在这项工作中，我们偏离了用于计算全息图的这种近似“理想”相干光传输模型。相反，我们从使用显示相机硬件系统测量的图像中了解真实显示与理想光传输的偏差。了解这种未知的光传播后，我们用它来补偿真实全息图像中的严重像差。所提出的硬件在环方法对空间、时间和硬件偏差具有鲁棒性，并且在信噪比和感知质量方面定性和定量地提高了现有方法的图像质量。我们在全息显示原型上验证了我们的方法，并表明该方法可以完全补偿未知像差以及错误和非线性 SLM 相位延迟，而无需对其进行显式建模。因此，所提出的方法在模拟和实验中显着优于现有的最先进方法 - 仅通过观察捕获的全息图像即可。
Holography is arguably the most promising technology to provide wide field-of-view compact eyeglasses-style near-eye displays for augmented and virtual reality. However, the image quality of existing holographic displays is far from that of current generation conventional displays, effectively making today's holographic display systems impractical. This gap stems predominantly from the severe deviations in the idealized approximations of the "unknown" light transport model in a real holographic display, used for computing holograms.In this work, we depart from such approximate "ideal" coherent light transport models for computing holograms. Instead, we learn the deviations of the real display from the ideal light transport from the images measured using a display-camera hardware system. After this unknown light propagation is learned, we use it to compensate for severe aberrations in real holographic imagery. The proposed hardware-in-the-loop approach is robust to spatial, temporal and hardware deviations, and improves the image quality of existing methods qualitatively and quantitatively in SNR and perceptual quality. We validate our approach on a holographic display prototype and show that the method can fully compensate unknown aberrations and erroneous and non-linear SLM phase delays, without explicitly modeling them. As a result, the proposed method significantly outperforms existing state-of-the-art methods in simulation and experimentation - just by observing captured holographic images.