Pyramid diffractive optical networks for unidirectional image magnification and demagnification.

ABSTRACT: Diffractive deep neural networks (D²NNs) are composed of successive transmissive layers optimized using supervised deep learning to all-optically implement various computational tasks between an input and output field-of-view. Here, we present a pyramid-structured diffractive optical network design (which we term P-D²NN), optimized specifically for unidirectional image magnification and demagnification. In this design, the diffractive layers are pyramidally scaled in alignment with the direction of the image magnification or demagnification. This P-D²NN design creates high-fidelity magnified or demagnified images in only one direction, while inhibiting the image formation in the opposite direction-achieving the desired unidirectional imaging operation using

SUBMITTER: Bai B 

PROVIDER: S-EPMC11291656 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature