{"title":"利用秩估计进行塔克张量分解，实现稀疏高光谱解混合","authors":"Ling Wu, Jie Huang, Zi-Yue Zhu","doi":"10.1080/01431161.2024.2357841","DOIUrl":null,"url":null,"abstract":"Hyperspectral image unmixing gives increasing focus on the structural integrity of the spatial-spectral information. A large number of methods exploit the sparse and low-rank properties of the abun...","PeriodicalId":14369,"journal":{"name":"International Journal of Remote Sensing","volume":"23 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tucker tensor decomposition with rank estimation for sparse hyperspectral unmixing\",\"authors\":\"Ling Wu, Jie Huang, Zi-Yue Zhu\",\"doi\":\"10.1080/01431161.2024.2357841\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hyperspectral image unmixing gives increasing focus on the structural integrity of the spatial-spectral information. A large number of methods exploit the sparse and low-rank properties of the abun...\",\"PeriodicalId\":14369,\"journal\":{\"name\":\"International Journal of Remote Sensing\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-06-16\",\"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/10.1080/01431161.2024.2357841\",\"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/10.1080/01431161.2024.2357841","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}
Tucker tensor decomposition with rank estimation for sparse hyperspectral unmixing
Hyperspectral image unmixing gives increasing focus on the structural integrity of the spatial-spectral information. A large number of methods exploit the sparse and low-rank properties of the abun...
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).
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