Pupil-Adaptive 3D Holography Beyond Coherent Depth-of-Field

TL;DR

This paper introduces a pupil-adaptive holographic display framework that dynamically adjusts depth-of-field effects based on eye pupil variations, significantly enhancing realism in 3D holography beyond traditional coherent methods.

Contribution

It presents a novel learning-based method to adapt holographic focus cues in real-time according to eye pupil shape and motion, bridging the gap between coherent and incoherent depth-of-field effects.

Findings

Improved depth-of-field depiction in simulations and prototypes.

Achieved at least 5 dB higher PSNR compared to existing methods.

Validated effectiveness through both simulations and experimental prototypes.

Abstract

Recent holographic display approaches propelled by deep learning have shown remarkable success in enabling high-fidelity holographic projections. However, these displays have still not been able to demonstrate realistic focus cues, and a major gap still remains between the defocus effects possible with a coherent light-based holographic display and those exhibited by incoherent light in the real world. Moreover, existing methods have not considered the effects of the observer's eye pupil size variations on the perceived quality of 3D projections, especially on the defocus blur due to varying depth-of-field of the eye. In this work, we propose a framework that bridges the gap between the coherent depth-of-field of holographic displays and what is seen in the real world due to incoherent light. To this end, we investigate the effect of varying shape and motion of the eye pupil on the quality of holographic projections, and devise a method that changes the depth-of-the-field of holographic projections dynamically in a pupil-adaptive manner. Specifically, we introduce a learning framework that adjusts the receptive fields on-the-go based on the current state of the observer's eye pupil to produce image effects that otherwise are not possible in current computer-generated holography approaches. We validate the proposed method both in simulations and on an experimental prototype holographic display, and demonstrate significant improvements in the depiction of depth-of-field effects, outperforming existing approaches both qualitatively and quantitatively by at least 5 dB in peak signal-to-noise ratio.