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We demonstrate that diffractive optical processors can be designed to produce arbitrary sets of spatially varying 3D point-spread functions (PSFs), allowing the implementation of any desired linear transformation between 3D input and output intensity distributions under incoherent illumination. Our results enable powerful new imaging functionalities such as snapshot 3D multispectral imaging, performed without mechanical scanning, spectral filtering, or digital postprocessing. By extending spatially varying, arbitrary PSF synthesis capability into the 3D domain, our work lays the foundation for 3D information processing using diffractive optical processors, enabling unique imaging and sensing capabilities that surpass the limitations of conventional optical systems.
Presenter
Univ. of California, Los Angeles (United States)
Md Sadman Sakib Rahman is a postdoctoral researcher at the Ozcan Research Group in UCLA, USA. He received his Ph.D. in Electrical and Computer Engineering from UCLA in 2024. He received his B.Sc. in 2014, and M.Sc. in 2017, both in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology. His research interest lies in deep learning, computational imaging, and optical information processing.