利用拓扑手性层状超结构实现快速选择性边缘增强成像

IF 16.3 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES National Science Review Pub Date : 2024-07-15 DOI:10.1093/nsr/nwae247
Wen Chen, Dong Zhu, Si-Jia Liu, Yi-Heng Zhang, Lin Zhu, Chao-Yi Li, Shi-Jun Ge, Peng Chen, Wan-Long Zhang, Xiao-Cong Yuan, Yan-Qing Lu
{"title":"利用拓扑手性层状超结构实现快速选择性边缘增强成像","authors":"Wen Chen, Dong Zhu, Si-Jia Liu, Yi-Heng Zhang, Lin Zhu, Chao-Yi Li, Shi-Jun Ge, Peng Chen, Wan-Long Zhang, Xiao-Cong Yuan, Yan-Qing Lu","doi":"10.1093/nsr/nwae247","DOIUrl":null,"url":null,"abstract":"Edge detection is a fundamental operation for feature extraction in the image processing. All-optical method arouses growing interest owing to its ultra-fast speed, low energy consumption and parallel computation. However, current optical edge detection is 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 external electric field, and respectively generates the vector beams with nearly orthogonal polarization distribution. Even after thousands of cycles, horizontal and vertical edges of the object are selectively enhanced with an ultra-fast switching time of about 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 potentials in the emerging frontiers of optical computing for artificial intelligence.","PeriodicalId":18842,"journal":{"name":"National Science Review","volume":"16 1","pages":""},"PeriodicalIF":16.3000,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast selective edge-enhanced imaging with topological chiral lamellar superstructures\",\"authors\":\"Wen Chen, Dong Zhu, Si-Jia Liu, Yi-Heng Zhang, Lin Zhu, Chao-Yi Li, Shi-Jun Ge, Peng Chen, Wan-Long Zhang, Xiao-Cong Yuan, Yan-Qing Lu\",\"doi\":\"10.1093/nsr/nwae247\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge detection is a fundamental operation for feature extraction in the image processing. All-optical method arouses growing interest owing to its ultra-fast speed, low energy consumption and parallel computation. However, current optical edge detection is 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 external electric field, and respectively generates the vector beams with nearly orthogonal polarization distribution. Even after thousands of cycles, horizontal and vertical edges of the object are selectively enhanced with an ultra-fast switching time of about 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 potentials in the emerging frontiers of optical computing for artificial intelligence.\",\"PeriodicalId\":18842,\"journal\":{\"name\":\"National Science Review\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":16.3000,\"publicationDate\":\"2024-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"National Science Review\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1093/nsr/nwae247\",\"RegionNum\":1,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"National Science Review","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1093/nsr/nwae247","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

边缘检测是图像处理中提取特征的基本操作。全光学方法因其超快的速度、低能耗和并行计算等优点而日益受到关注。然而,目前的光学边缘检测一般仅限于静态设备和固定功能。在此,我们提出了一种基于铁电液晶拓扑结构的快速切换方案。自组装的手性片状上层结构由方位变化的光配向剂引导,可受外部电场极性的动态控制,分别产生近乎正交偏振分布的矢量光束。即使经过数千次循环,物体的水平和垂直边缘也能在约 57 μs 的超快切换时间内得到选择性增强。宽带边缘增强成像得到了有效展示。这项工作扩展了拓扑螺旋超结构的巧妙构建,并让人们看到了它们在新兴的人工智能光学计算前沿领域的重要潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Fast selective edge-enhanced imaging with topological chiral lamellar superstructures
Edge detection is a fundamental operation for feature extraction in the image processing. All-optical method arouses growing interest owing to its ultra-fast speed, low energy consumption and parallel computation. However, current optical edge detection is 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 external electric field, and respectively generates the vector beams with nearly orthogonal polarization distribution. Even after thousands of cycles, horizontal and vertical edges of the object are selectively enhanced with an ultra-fast switching time of about 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 potentials in the emerging frontiers of optical computing for artificial intelligence.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
National Science Review
National Science Review MULTIDISCIPLINARY SCIENCES-
CiteScore
24.10
自引率
1.90%
发文量
249
审稿时长
13 weeks
期刊介绍: National Science Review (NSR; ISSN abbreviation: Natl. Sci. Rev.) is an English-language peer-reviewed multidisciplinary open-access scientific journal published by Oxford University Press under the auspices of the Chinese Academy of Sciences.According to Journal Citation Reports, its 2021 impact factor was 23.178. National Science Review publishes both review articles and perspectives as well as original research in the form of brief communications and research articles.
期刊最新文献
Ultraslow spreading ridges: slowest but locally thickest. Origin of sulfate in post-snowball-Earth oceans: river inputs vs. shelf-derived H2S. Deciphering decadal urban ozone trends from historical records since 1980. Contribution of irrigation to the production of maize, wheat, and rice in the major global producing countries. Fossil evidence for silica biomineralization in Permian lycophytes.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1