Stochastic Light Field Holography

TL;DR

This paper introduces a novel hologram generation algorithm that improves 3D hologram realism by optimizing pupil sampling and light transport, enhancing the viewing experience for holographic displays.

Contribution

The work presents a new method matching incoherent Light Field and coherent Wigner Function transport, supervised by synthesized photographs, to improve hologram realism.

Findings

Enhanced parallax and focus cues in holograms

Significant improvement over state-of-the-art algorithms

Better realism across various pupil states

Abstract

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.