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@article{194719,
        author = {Tanvi Handa and Kajal Rathore},
        title = {Holographic Technology: Evolutionary Architecture, Deep Learning Optimisation, and Cross-Domain Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {5261-5272},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194719},
        abstract = {Holography, originally conceived by Dennis Gabor in 1948 as a mechanism to improve electron microscope resolution, has undergone a profound evolution from analogue film-based recording to computationally intensive, AI-accelerated digital systems. Unlike stereoscopic displays that simulate depth through binocular disparity alone, coherent-optics-based holography reconstructs complete light wavefronts, delivering genuine motion parallax and physiologically comfortable depth perception. This paper presents a comprehensive survey and architectural design for a deployable holographic display system, spanning the physical optics layer, computer-generated holography (CGH) algorithms, deep-learning-based phase optimisation, spatial light modulator (SLM) hardware, and experimental validation. We introduce a proposed system architecture integrating a 532 nm diode-pumped solid-state laser, a liquid-crystal-on-silicon (LCoS) SLM operating at 4K resolution, and a U-Net-based neural CGH pipeline achieving real-time rendering at 60 fps with a peak signal-to-noise ratio (PSNR) exceeding 31 dB. A comparative review of twelve representative Scopus- and IEEE-indexed studies published between 1948 and 2025 contextualises the contribution within the current research landscape. The global digital holography market, valued at approximately USD 5.21 billion in 2025, is projected to reach USD 28.05 billion by 2035, and this work maps prospective application trajectories in surgical planning, automotive head-up displays (HUDs), augmented reality (AR) wearables, and holographic telepresence. Our findings confirm that convergence of metasurface fabrication, edge-AI acceleration, and sub-terahertz wireless bandwidth is the decisive enabler for mass-market holographic devices by 2030.},
        keywords = {Computer-Generated Holography (CGH), Metasurface, Deep Learning, Holographic Telepresence, Augmented Reality, Digital Holographic Microscopy.},
        month = {March},
        }