Abstract
Optical analog computing overcomes the throughput and computational speed limitations of traditional digital computing, facilitating salient object detection on platforms that rapidly process massive image data, such as optical remote sensing. Further device miniaturization and integration can be achieved by replacing filters in optical analog computing with metasurface. Based on the combination of optical analog computing and dielectric metasurface, we proposed an optical analog cross-correlation operation operating in the mid-infrared wavelength band to achieve the real-time and compact salient object detection. Even in extremely complex scenes, this cross-correlation operation can be used to identify and segment target patterns based on several target features accurately. The proposed optical analog cross-correlation operation may find applications in object tracking, medical image segmentation, and person re-identification.
Published Version
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