Wirtinger Holography for Near-Eye Displays
Wirtinger Holography for Near-Eye Displays
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DOI：
10.1145/3355089.3356539
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发表时间：
2019-11-01
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;Peng, Yifan;Heide, Felix
使用全息投影的近眼显示器正在作为一种令人兴奋的显示方法，用于在没有复杂的光学设置的情况下进行虚拟和增强现实 - 将光学复杂性转移到计算。尽管可以使用精确的相调制硬件，但阶段检索算法仍处于起步阶段，全息图显示方法诉诸于启发式编码方法或依靠各种放松的迭代方法。通过重新访问复杂的电线导数，在给定时间单个深度的场景全息图的问题。我们还讨论将框架扩展到渲染3D体积场景。使用Wirtinger衍生物使我们能够将相位检索问题作为二次问题，可以使用一阶优化方法最小化。所提出的Wiretinger全息图是灵活的，并促进了不同损失函数的使用，包括通过深神经网络参数的学习感知损失以及随机优化方法。我们通过在仿真和实验硬件原型中证明误差较低的全息重建来验证该框架。
Near-eye displays using holographic projection are emerging as an exciting display approach for virtual and augmented reality at high-resolution without complex optical setups - shifting optical complexity to computation. While precise phase modulation hardware is becoming available, phase retrieval algorithms are still in their infancy, and holographic display approaches resort to heuristic encoding methods or iterative methods relying on various relaxations.In this work, we depart from such existing approximations and solve the phase retrieval problem for a hologram of a scene at a single depth at a given time by revisiting complex Wirtinger derivatives. We also discuss extending our framework to render 3D volumetric scenes. Using Wirtinger derivatives allows us to pose the phase retrieval problem as a quadratic problem which can be minimized with first-order optimization methods. The proposed Wirtinger Holography is flexible and facilitates the use of different loss functions, including learned perceptual losses parametrized by deep neural networks, as well as stochastic optimization methods. We validate this framework by demonstrating holographic reconstructions with an order of magnitude lower error, both in simulation and on an experimental hardware prototype.