{"id":239052,"date":"2026-06-16T07:25:09","date_gmt":"2026-06-16T12:25:09","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2026\/06\/light-programmed-system-projects-28-layer-3d-images-in-single-shot"},"modified":"2026-06-16T07:25:09","modified_gmt":"2026-06-16T12:25:09","slug":"light-programmed-system-projects-28-layer-3d-images-in-single-shot","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2026\/06\/light-programmed-system-projects-28-layer-3d-images-in-single-shot","title":{"rendered":"Light-programmed system projects 28-layer 3D images in single shot"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/light-programmed-system-projects-28-layer-3d-images-in-single-shot2.jpg\"><\/a><\/p>\n<p>Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan Ozcan, introduced a snapshot 3D image projection system that integrates a digital encoder with a passive diffractive optical decoder, jointly optimized end-to-end through deep learning. The hybrid architecture projects multiple distinct images onto closely spaced axial planes in a single shot, marking a significant step toward compact, high-fidelity volumetric display technologies. The research is <a href=\"https:\/\/www.nature.com\/articles\/s41377-026-02378-3\" target=\"_blank\">published<\/a> in the journal Light: Science &amp; Applications.<\/p>\n<p>3D image display technology is essential for next-generation holography, immersive visualization, and augmented and virtual reality (AR\/VR) interfaces, where accurate focal cues across depth are critical for natural depth perception and visual comfort. However, dense depth multiplexing in conventional holographic displays remains a challenge: As the axial image planes approach one another in the output volume, diffraction-induced crosstalk rapidly degrades depth selectivity and image fidelity.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan Ozcan, introduced a snapshot 3D image projection system that integrates a digital encoder with a passive diffractive optical decoder, jointly optimized end-to-end through deep learning. The hybrid architecture projects multiple distinct images onto closely spaced axial planes in [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1498,6,1491,1879],"tags":[],"class_list":["post-239052","post","type-post","status-publish","format-standard","hentry","category-augmented-reality","category-robotics-ai","category-transportation","category-virtual-reality"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/239052","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=239052"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/239052\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=239052"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=239052"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=239052"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}