{"title":"生物视觉启发的全色和异色传感钙钛矿智能相机。","authors":"Yu Li,Zikun Jin,Yujin Liu,Jian Wang,Shanshan Yu,Jingyang Xing,Jieuyu Tian,Xuyin Ding,Min Zhang,Qian Li,Zhong Ji,Xueli Chen,Shihe Yang","doi":"10.1002/adma.202508984","DOIUrl":null,"url":null,"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.","PeriodicalId":114,"journal":{"name":"Advanced Materials","volume":"96 1","pages":"e08984"},"PeriodicalIF":26.8000,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Biovision-Inspired Perovskite Intelligent Camera for Panchromatic and Metameric Sensing.\",\"authors\":\"Yu Li,Zikun Jin,Yujin Liu,Jian Wang,Shanshan Yu,Jingyang Xing,Jieuyu Tian,Xuyin Ding,Min Zhang,Qian Li,Zhong Ji,Xueli Chen,Shihe Yang\",\"doi\":\"10.1002/adma.202508984\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":114,\"journal\":{\"name\":\"Advanced Materials\",\"volume\":\"96 1\",\"pages\":\"e08984\"},\"PeriodicalIF\":26.8000,\"publicationDate\":\"2025-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Materials\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1002/adma.202508984\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/adma.202508984","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Biovision-Inspired Perovskite Intelligent Camera for Panchromatic and Metameric Sensing.
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.
期刊介绍:
Advanced Materials, one of the world's most prestigious journals and the foundation of the Advanced portfolio, is the home of choice for best-in-class materials science for more than 30 years. Following this fast-growing and interdisciplinary field, we are considering and publishing the most important discoveries on any and all materials from materials scientists, chemists, physicists, engineers as well as health and life scientists and bringing you the latest results and trends in modern materials-related research every week.