Holographic displays promise unprecedented capabilities for direct-view displays as well as virtual and augmented reality applications. However, one of the biggest challenges for computer-generated holography (CGH) is the fundamental tradeoff between algorithm runtime and achieved image quality. Moreover, the image quality achieved by most holographic displays is low, due to the mismatch between the optical wave propagation of the display and its simulated model. We develop an algorithmic CGH framework that achieves unprecedented image fidelity and real-time framerates. Our framework comprises several parts, including a novel camera-in-the-loop optimization strategy that allows us to either optimize a hologram directly or train an interpretable model of the optical wave propagation and a neural network architecture that represents the first CGH algorithm capable of generating full-color high-quality holographic images at FHD resolution in real-time. Based on this framework, we further propose a holographic display architecture using two SLMs, where the camera-in-the-loop optimization with an automated calibration procedure is applied. As such, both diffracted and undiffracted light on the target plane are acquired to update hologram patterns on SLMs simultaneously. The experimental demonstration delivers higher contrast and less noisy holographic images without the need for extra filtering, compared to conventional single SLM-based systems. In summary, we envision that bringing artificial intelligence advances into conventional optics/photonics research opens many opportunities to both communities and is promising to enable high fidelity imaging and display solutions.
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Bio: Yifan (Evan) Peng is a Postdoctoral Research Fellow at Stanford University in Computational Imaging Lab. His research interest rides across the interdisciplinary fields of optics/photonics, computer graphics, and computer vision. Much of his recent work concerns developing computational imaging modalities combining optics and algorithms, for both cameras and displays. He completed his Ph.D. in Computer Science at the University of British Columbia, and his M.Sc. and B.E. in Optical Science and Engineering at Zhejiang University. During the Ph.D. career, he was also a Visiting Research Student at Stanford Computational Imaging Lab and at Visual Computing Center, King Abdullah University of Science and Technology. He has recently served professional roles as committees and reviewers for several venues of IEEE, OSA, SPIE, and SID.