The popularity of deep learning has boosted computer-generated holography(CGH)as a vibrant research field,particularly physics-driven unsupervised learning.Nevertheless,present unsupervised CGH models have not yet exp...The popularity of deep learning has boosted computer-generated holography(CGH)as a vibrant research field,particularly physics-driven unsupervised learning.Nevertheless,present unsupervised CGH models have not yet explored the potential of generating full-color 3D holograms through a unified framework.In this study,we propose a lightweight multiwavelength network model capable of high-fidelity and efficient full-color hologram generation in both 2D and 3D display,called IncepHoloRGB.The high-speed simultaneous generation of RGB holograms at 191 frames per second(FPS)is based on Inception sampling blocks and multi-wavelength propagation module integrated with depth-traced superimposition,achieving an average structural similarity(SSIM)of 0.88 and peak signal-to-noise ratio(PSNR)of 29.00 on the DIV2K test set in reconstruction.Full-color reconstruction of numerical simulations and optical experiments shows that IncepHoloRGB is versatile to diverse scenarios and can obtain authentic full-color holographic 3D display within a unified network model,paving the way for applications towards real-time dynamic naked-eye 3D display,virtual and augmented reality(VR/AR)systems.展开更多
基金supports from National Natural Science Foundation of China(Grant No.62205117,52275429)National Key Research and Development Program of China(Grant No.2021YFF0502700)+2 种基金Young Elite Scientists Sponsorship Program by CAST(Grant No.2022QNRC001)West Light Foundation of the Chinese Academy of Sciences(Grant No.xbzg-zdsys-202206)Hubei Natural Science Foundation Innovative Research Group Project(2024AFA025).
文摘The popularity of deep learning has boosted computer-generated holography(CGH)as a vibrant research field,particularly physics-driven unsupervised learning.Nevertheless,present unsupervised CGH models have not yet explored the potential of generating full-color 3D holograms through a unified framework.In this study,we propose a lightweight multiwavelength network model capable of high-fidelity and efficient full-color hologram generation in both 2D and 3D display,called IncepHoloRGB.The high-speed simultaneous generation of RGB holograms at 191 frames per second(FPS)is based on Inception sampling blocks and multi-wavelength propagation module integrated with depth-traced superimposition,achieving an average structural similarity(SSIM)of 0.88 and peak signal-to-noise ratio(PSNR)of 29.00 on the DIV2K test set in reconstruction.Full-color reconstruction of numerical simulations and optical experiments shows that IncepHoloRGB is versatile to diverse scenarios and can obtain authentic full-color holographic 3D display within a unified network model,paving the way for applications towards real-time dynamic naked-eye 3D display,virtual and augmented reality(VR/AR)systems.
