Real-time vision-extended holographic near-eye display system based on perceptual range-adaptive visualization architecture
• Real-time holographic NED proposed based on PRaV architecture using OAC module and accelerated random-phase ASM. • PRaV handles the entire operation including selective holographic visualizations through intuitive eye-commands. • Accelerated random-phase ASM with efficient parallel normalization provides real-time computation for CGH generation. • An effective human-computer interaction ensures continuous and immersive holographic experiences with minimized data loss. • In the experiment, high-fidelity holographic contents that are fit for next-generation wearable displays are visualized. We propose an intelligent real-time holographic near-eye display (NED) system based on a perceptual range-adaptive visualization (PRaV) architecture, which incorporates a dynamic ocular-actuated controlling (OAC) module for intuitive, hands-free interaction. The PRaV architecture handles the entire operation of the system, including real-time acquisition and holographic rendering of real-world scenes with vision-extended visualizations including both full-field holographic images and selectively highlighted regions-of-interest (RoI), based on user eye commands. These eye-dependent commands, interpreted by the OAC module, dynamically trigger transitions between full-field and highlighted holographic visualizations, thereby extending perceptual capabilities beyond natural human vision. To ensure seamless high-speed computer-generated hologram (CGH) generation within the display pipeline, the system employs an accelerated random-phase angular spectrum method (ASM) using a parallel normalization technique. The core functionality of the proposed system is the unified integration of hardware and software components to deliver continuous and immersive user experience with the PRaV architecture. Experimental results confirm that the proposed system achieves high-fidelity and low-latency performance in real-time range-adaptive holographic visualization, laying the groundwork for future development of hands-free head-mounted display applications.
Authors
- Ki‐Chul Kwon (ORCID: https://orcid.org/0000-0003-0334-504X)
- Khongorzul Dashdondov (ORCID: https://orcid.org/0000-0001-5113-8542)
- Tuvshinjargal Amgalan (ORCID: https://orcid.org/0000-0003-3411-1617)
- Anar Khuderchuluun (ORCID: https://orcid.org/0000-0001-6058-7200)
- Munkh‐Uchral Erdenebat (ORCID: https://orcid.org/0000-0001-6941-8577)
- Erkhembaatar Dashdavaa (ORCID: https://orcid.org/0000-0001-5055-3410)
- Nam Kim (ORCID: https://orcid.org/0000-0001-8109-2055)
- Ganbat Baasantseren (ORCID: https://orcid.org/0000-0003-1895-0787)
- Hui‐Ying Wu (ORCID: https://orcid.org/0009-0006-2612-5620)
Institutions
- Chungbuk National University (KR)
- Kyungpook National University (KR)
- Korea Electronics Technology Institute (KR)
- National University of Mongolia (MN)
Publication Details
- Journal
- Optics & Laser Technology
- Published
- 2025-10-25
- DOI
- https://doi.org/10.1016/j.optlastec.2025.114145
- Citations
- 1
- Primary Topic
- Advanced Optical Imaging Technologies
- Type
- article
- Field-Weighted Citation Impact
- 1.14