Concurrent Image Differentiation and Integration Processings Enabled By Polarization-Multiplexed Metasurface

Optical computing and image processing performed by sensor front-end metasurfaces is receiving increasing interest because of advantages such as significant reduction of latency time, energy consumption, and system complexity. Despite the rapid progress, concurrent processing, the most important feature of electronic computing, has not yet been well implemented in optical computing. Here, a metasurface-based optical image processor that can perform optical differentiation and integration tasks simultaneously is proposed. This optical front-end processor integrates two coherent transfer functions corresponding to differential and integral convolution kernels into a built-in metasurface by polarization encoding, allowing concurrent processing of multiple all-optical computational tasks. The simultaneous differentiation and integration operations on images for edge enhancement and denoising are demonstrated at multiple visible wavelengths. This concurrent processing architecture paves a promising pathway toward multifunctional and higher-speed image processing for machine vision and biomedical imaging and shows the potential to expedite and potentially supplant certain digital neural network algorithms.