All-optical image classification through unknown random diffusers using a single-pixel diffractive network.

ABSTRACT: Classification of an object behind a random and unknown scattering medium sets a challenging task for computational imaging and machine vision fields. Recent deep learning-based approaches demonstrated the classification of objects using diffuser-distorted patterns collected by an image sensor. These methods demand relatively large-scale computing using deep neural networks running on digital computers. Here, we present an all-optical processor to directly classify unknown objects through unknown, random phase diffusers using broadband illumination detected with a single pixel. A set of transmissive diffractive layers, optimized using deep learning, forms a physical network that all-optically maps the spatial information of an input object behind a random diffuser into the power spectrum o

SUBMITTER: Bai B 

PROVIDER: S-EPMC9998891 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature