Litcius/Paper detail

In-situ and ex-situ twisted bilayer liquid crystal computing platform for reconfigurable image processing

Kang Zeng, Yougang Ke, Zhangming Hong, Linzhou Zeng, Xinxing Zhou

2025Opto-Electronic Advances14 citationsDOIOpen Access PDF

Abstract

All-optical image processing has been viewed as a promising technique for its high computation speed and low power consumption. However, current methods are often restricted to few functionalities and low reconfigurabilities, which cannot meet the growing demand for device integration and scenario adaptation in next-generation vision regimes. Here, we propose and experimentally demonstrate a bilayer liquid crystal computing platform for reconfigurable image processing. Under different in-situ/ex-situ twisted/untwisted conditions of the layers, our approach allows for eight kinds of image processing functions, including one/two-channel bright field imaging, one/two-channel vortex filtering, horizontally/vertically one-dimensional edge detection, vertex detection, and photonic spin Hall effect-based resolution adjustable edge detection. A unified theoretical framework for this scheme is established on the transfer function theory, which coincides well with the experimental results. The proposed method offers an easily-switchable multi-functional solution to optical image processing by introducing mechanical degrees of freedom, which may enable emerging applications in computer vision, autonomous driving, and biomedical microscopy.

Topics & Concepts

Image processingComputationBilayerComputer scienceEdge detectionOptical computingEnhanced Data Rates for GSM EvolutionDigital image processingEdge computingPower (physics)Field (mathematics)Vertex (graph theory)Adaptation (eye)Scheme (mathematics)Unconventional computingPhotonicsLiquid crystalComputer visionComputational scienceMachine visionImage resolutionImage (mathematics)OpticsFunction (biology)Parallel processingMaterials scienceVortexEdge enhancementAdvanced Materials and MechanicsLiquid Crystal Research AdvancementsNeural Networks and Reservoir Computing