{"title":"用于无监督合成孔径雷达图像变化检测的基于全局斑块相似性的图形","authors":"Jun Wang, Fei Zeng, Anjun Zhang, Ting You","doi":"10.1080/2150704x.2024.2327085","DOIUrl":null,"url":null,"abstract":"This letter presents a novel method for synthetic aperture radar (SAR) image change detection using the global patch similarity-based graph (GPSG). First, the SAR image is divided into a number of ...","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"255 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A global patch similarity-based graph for unsupervised SAR image change detection\",\"authors\":\"Jun Wang, Fei Zeng, Anjun Zhang, Ting You\",\"doi\":\"10.1080/2150704x.2024.2327085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter presents a novel method for synthetic aperture radar (SAR) image change detection using the global patch similarity-based graph (GPSG). First, the SAR image is divided into a number of ...\",\"PeriodicalId\":49132,\"journal\":{\"name\":\"Remote Sensing Letters\",\"volume\":\"255 1\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/2150704x.2024.2327085\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Letters","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/2150704x.2024.2327085","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
A global patch similarity-based graph for unsupervised SAR image change detection
This letter presents a novel method for synthetic aperture radar (SAR) image change detection using the global patch similarity-based graph (GPSG). First, the SAR image is divided into a number of ...
期刊介绍:
Remote Sensing Letters is a peer-reviewed international journal committed to the rapid publication of articles advancing the science and technology of remote sensing as well as its applications. The journal originates from a successful section, of the same name, contained in the International Journal of Remote Sensing from 1983 –2009. Articles may address any aspect of remote sensing of relevance to the journal’s readership, including – but not limited to – developments in sensor technology, advances in image processing and Earth-orientated applications, whether terrestrial, oceanic or atmospheric. Articles should make a positive impact on the subject by either contributing new and original information or through provision of theoretical, methodological or commentary material that acts to strengthen the subject.