Snapshot 3D image projection using a diffractive decoder

Işıl et al. Light: Science & Applications (2026)15:270 https://doi.org/10.1038/s41377-026-02378-3 www.nature.com/lsa ARTICLE Open Access Snapshot 3D image projection using a diffractive decoder 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Çağatay Işıl1,2,3, Alexander Chen1, Yuhang Li Aydogan Ozcan 1,2,3 ✉ 1,2,3 , F. Onuralp Ardic 1 , Shiqi Chen 1,2,3 , Che-Yung Shen 1,2,3 and Abstract 3D image display is essential for next-generation volumetric imaging; however, dense depth multiplexing for 3D image projection remains challenging because diffraction-induced cross-talk rapidly increases as the axial image planes get closer. Here, we introduce a 3D display system comprising a digital encoder and a diffractive decoder, which simultaneously projects different images onto multiple target axial planes with high axial resolution. By leveraging multi-layer diffractive wavefront decoding and deep learning-based end-to-end optimization, the system achieves high-fidelity depth-resolved 3D image projection in a snapshot, enabling axial plane separations on the order of a wavelength. The digital encoder leverages a Fourier encoder network to capture multi-scale spatial and frequency-domain features from input images, integrates axial position encoding, and generates a unified phase representation that simultaneously encodes all images to be axially projected in a single snapshot through a jointlyoptimized diffractive decoder. We characterized the impact of diffractive decoder depth, output diffraction efficiency, spatial light modulator resolution, and axial encoding density, revealing trade-offs that govern axial separation and 3D image projection quality. We further demonstrated the capability to display volumetric images containing 28 axial slices, as well as the ability to dynamically reconfigure the axial locations of the image planes, performed on demand. Finally, we experimentally validated a two-plane optical prototype using a single-layer physical decoder, demonstrating close agreement between the measured results and the target images. These results establish the diffractive 3D display system as a compact and scalable framework for depth-resolved snapshot 3D image projection, with potential applications in holographic displays, AR/VR interfaces, and volumetric optical computing. Introduction Three-dimensional (3D) display has emerged as a foundational technology for next-generation holography, immersive visualization, and volumetric interfaces in AR/ VR systems1–5. By delivering accurate focal cues across depth, 3D displays can provide more natural focus accommodation and alleviate vergence–accommodation conflict compared with conventional 2D screens, thereby improving depth perception and visual comfort. To achieve high-fidelity 3D volumetric display, a diverse Correspondence: Aydogan Ozcan () 1 Electrical and Computer Engineering Department, University of California, Los Angeles, CA, USA 2 Bioengineering Department, University of California, Los Angeles, CA, USA Full list of author information is available at the end of the article These authors contributed equally: Çağatay Işıl, Alexander Chen, Yuhang Li range of paradigms has been explored, spanning volumetric displays based on microbubble voxels6, acoustic trapping7, or photophoretic optical trapping8, light-field architectures such as lenticular lenslets and nanophotonic arrays9, as well as holographic displays that directly encode wavefronts to synthesize objects in free space10. Among these, holographic displays have been widely investigated due to their inherent ability to display highresolution 3D images by providing phase and amplitude control of the optical field11–14. However, achieving high axial resolution across multiple closely spaced depth planes remains a challenging task. As the axial image plane spacing decreases, diffraction-induced inter-plane coupling causes severe cross-talk, degrading depth selectivity and display fidelity15. These limitations stem from the insufficient degrees of freedom (DoF) available in © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Işıl et al. Light: Science & Applications (2026)15:270 conventional single-plane modulators, which cannot simultaneously satisfy the complex field requirements of multiple axial depths10. Consequently, practical holographic displays are bound by fundamental trade-offs between axial resolution, signal-to-noise ratio, and the space-bandwidth product of the system. A wide range of computational holography algorithms has been developed to synthesize volumetric holograms with improved accuracy and color performance, forming an important algorithmic foundation of modern digital holographic displays11,16–19. More recently, learningbased methods have been incorporated into holographic and 3D display pipelines to enable data-driven wavefront generation, phase optimization, and end-to-end codesign, often improving display quality and computational efficiency20–23. While computational holography algorithms have significantly improved volumetric wavefront generation, their performance remains strictly governed by the hardware-limited DoF of spatial light modulators (SLMs). Recent optical augmentation strategies have introduced additional diffractive transformations to expand the effective DoF of the optical system, including active control of volume speckle fields and learned diffractive optics that extend system capability beyond an SLM-only pipeline24–26. Here, we present a snapshot 3D display system that integrates a digital encoder jointly optimized with a passive diffractive decoder composed of trainable phase layers. Within this framework, a learned diffractive decoder is co-designed with digital hologram synthesis through an encoder neural network to improve depthdependent field shaping for snapshot 3D image projection over a desired volume. The digital encoder utilizes a Fourier-based network to extract multi-scale spatial and frequency features from input images, incorporates axial position information, and produces a single-phase representation that simultaneously encodes all input images for one-shot axial proje (...truncated)