Deep learning-based incoherent holographic camera enabling acquisition of real-world holograms for holographic streaming system.

ABSTRACT: While recent research has shown that holographic displays can represent photorealistic 3D holograms in real time, the difficulty in acquiring high-quality real-world holograms has limited the realization of holographic streaming systems. Incoherent holographic cameras, which record holograms under daylight conditions, are suitable candidates for real-world acquisition, as they prevent the safety issues associated with the use of lasers; however, these cameras are hindered by severe noise due to the optical imperfections of such systems. In this work, we develop a deep learning-based incoherent holographic camera system that can deliver visually enhanced holograms in real time. A neural network filters the noise in the captured holograms, maintaining a complex-valued hologram format through

SUBMITTER: Yu H 

PROVIDER: S-EPMC10267150 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature