材料科学
RGB颜色模型
机器视觉
遥感
人工智能
计算机视觉
多光谱图像
计算机科学
地质学
作者
Yu Li,Zikun Jin,Yujin Liu,Jian Wang,Shanshan Yu,Jingyang Xing,Jie Tian,Xuyin Ding,Min Zhang,Qian Li,Zhong Ji,Xueli Chen,Shihe Yang
标识
DOI:10.1002/adma.202508984
摘要
Abstract Biological vision systems excel at acquiring and processing information, but there is often a trade‐off between these capabilities. For instance, mantis shrimp possess exceptional spectral sensing but poor color perception due to limited neural processing. Taking the best of both worlds, the mantis shrimp's spectral detection ability and the human‐like visual processing power are integrated to achieve full‐color perception. Using an aerosol‐liquid‐solid spraying technique, an array of high‐quality, excess ion migration enhanced perovskite narrowband photodetectors spanning the ultraviolet to visible spectrum is developed. These detectors enable a computational multispectral imaging system that captures seven spectral images in one shot. A deep‐learning‐based color fusion network is designed to efficiently translate multispectral inputs into an RGB representation, significantly enhancing color recognition of these mantis shrimp‐inspired multispectral cameras and affording the capability to overcome metamerism. These perovskite intelligent camera leverages the strengths of biological vision and demonstrate a novel approach to multispectral imaging that could advance applications in machine vision, remote sensing, and medical imaging.
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