{"title":"基于自适应背景字典构建和协作表示的高光谱异常检测","authors":"Mingming Xu, Jinhao Zhang, Shanwei Liu, Hui Sheng","doi":"10.1080/01431161.2024.2343431","DOIUrl":null,"url":null,"abstract":"Collaborative representation-based (CR) methods have received widespread attention in hyperspectral anomaly detection, but the results are greatly affected by the quality of the background dictiona...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"18 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hyperspectral anomaly detection based on adaptive background dictionary construction and collaborative representation\",\"authors\":\"Mingming Xu, Jinhao Zhang, Shanwei Liu, Hui Sheng\",\"doi\":\"10.1080/01431161.2024.2343431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Collaborative representation-based (CR) methods have received widespread attention in hyperspectral anomaly detection, but the results are greatly affected by the quality of the background dictiona...\",\"PeriodicalId\":14369,\"journal\":{\"name\":\"International Journal of Remote Sensing\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/01431161.2024.2343431\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/01431161.2024.2343431","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
Hyperspectral anomaly detection based on adaptive background dictionary construction and collaborative representation
Collaborative representation-based (CR) methods have received widespread attention in hyperspectral anomaly detection, but the results are greatly affected by the quality of the background dictiona...
期刊介绍：
The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include:
• Remotely sensed data collection, analysis, interpretation and display.
• Surveying from space, air, water and ground platforms.
• Imaging and related sensors.
• Image processing.
• Use of remotely sensed data.
• Economic surveys and cost-benefit analyses.
• Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
