Simultaneous Color Computer Generated Holography

Computer generated holography has long been touted as the future of augmented and virtual reality (AR/VR) displays, but has yet to be realized in practice. Previous high-quality, color holographic displays have made either a 3$\times$ sacrifice on frame rate by using a sequential color illumination scheme or used more than one spatial light modulator (SLM) and/or bulky, complex optical setups. The reduced frame rate of sequential color introduces distracting judder and color fringing in the presence of head motion while the form factor of current simultaneous color systems is incompatible with a head-mounted display. In this work, we propose a framework for simultaneous color holography that allows the use of the full SLM frame rate while maintaining a compact and simple optical setup. Simultaneous color holograms are optimized through the use of a perceptual loss function, a physics-based neural network wavefront propagator, and a camera-calibrated forward model. We measurably improve hologram quality compared to other simultaneous color methods and move one step closer to the realization of color holographic displays for AR/VR

Stochastic Light Field Holography

The Visual Turing Test is the ultimate goal to evaluate the realism of holographic displays. Previous studies have focused on addressing challenges such as limited \'etendue and image quality over a large focal volume, but they have not investigated the effect of pupil sampling on the viewing experience in full 3D holograms. In this work, we tackle this problem with a novel hologram generation algorithm motivated by matching the projection operators of incoherent Light Field and coherent Wigner Function light transport. To this end, we supervise hologram computation using synthesized photographs, which are rendered on-the-fly using Light Field refocusing from stochastically sampled pupil states during optimization. The proposed method produces holograms with correct parallax and focus cues, which are important for passing the Visual Turing Test. We validate that our approach compares favorably to state-of-the-art CGH algorithms that use Light Field and Focal Stack supervision. Our experiments demonstrate that our algorithm significantly improves the realism of the viewing experience for a variety of different pupil states

Media 2: High spatio-temporal resolution video with compressed sensing

Originally published in Optics Express on 15 June 2015 (oe-23-12-15992

Media 3: High spatio-temporal resolution video with compressed sensing

Originally published in Optics Express on 15 June 2015 (oe-23-12-15992

Neural \'{E}tendue Expander for Ultra-Wide-Angle High-Fidelity Holographic Display

Holographic displays can generate light fields by dynamically modulating the wavefront of a coherent beam of light using a spatial light modulator, promising rich virtual and augmented reality applications. However, the limited spatial resolution of existing dynamic spatial light modulators imposes a tight bound on the diffraction angle. As a result, today's holographic displays possess low \'{e}tendue, which is the product of the display area and the maximum solid angle of diffracted light. The low \'{e}tendue forces a sacrifice of either the field of view (FOV) or the display size. In this work, we lift this limitation by presenting neural \'{e}tendue expanders. This new breed of optical elements, which is learned from a natural image dataset, enables higher diffraction angles for ultra-wide FOV while maintaining both a compact form factor and the fidelity of displayed contents to human viewers. With neural \'{e}tendue expanders, we achieve 64$\times$ \'{e}tendue expansion of natural images with reconstruction quality (measured in PSNR) over 29dB on simulated retinal-resolution images. As a result, the proposed approach with expansion factor 64$\times$ enables high-fidelity ultra-wide-angle holographic projection of natural images using an 8K-pixel SLM, resulting in a 18.5 mm eyebox size and 2.18 steradians FOV, covering 85\% of the human stereo FOV

Media 4: High spatio-temporal resolution video with compressed sensing

Originally published in Optics Express on 15 June 2015 (oe-23-12-15992