Fast selective edge-enhanced imaging with topological chiral lamellar superstructures

Abstract

ABSTRACT Edge detection is a fundamental operation for feature extraction in image processing. The all-optical method has aroused growing interest owing to its ultra-fast speed, low energy consumption and parallel computation. However, current optical edge detection methods are generally limited to static devices and fixed functionality. Herein, we propose a fast-switchable scheme based on a ferroelectric liquid crystal topological structure. The self-assembled chiral lamellar superstructure, directed by the azimuthally variant photo-alignment agent, can be dynamically controlled by the polarity of the external electric field and respectively generates the vector beams with nearly orthogonal polarization distribution. Even after thousands of cycles, the horizontal and vertical edges of the object are selectively enhanced with an ultra-fast switching time of ∼57 μs. Broadband edge-enhanced imaging is efficiently demonstrated. This work extends the ingenious building of topological heliconical superstructures and offers an important glimpse into their potential in the emerging frontiers of optical computing for artificial intelligence.