{"title":"基于SIFT的遥感影像配准","authors":"Wang Kai, C. Bo","doi":"10.1109/ICFCSA.2011.28","DOIUrl":null,"url":null,"abstract":"this paper applies one kind of methods of automatic image registration, Scale Invariant Feature Transform(SIFT), into the region of remote sensing images. It has been found that SIFT can extract the features invariant to scale and rotation with specific key point descriptors as matching points for the registration of remote sensing images. Experimental results are discussed in the last part of this paper, and has confirmed the validity of the proposed method.","PeriodicalId":141108,"journal":{"name":"2011 International Conference on Future Computer Sciences and Application","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"SIFT Based Registration of Remotely-Sensed Imagery\",\"authors\":\"Wang Kai, C. Bo\",\"doi\":\"10.1109/ICFCSA.2011.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"this paper applies one kind of methods of automatic image registration, Scale Invariant Feature Transform(SIFT), into the region of remote sensing images. It has been found that SIFT can extract the features invariant to scale and rotation with specific key point descriptors as matching points for the registration of remote sensing images. Experimental results are discussed in the last part of this paper, and has confirmed the validity of the proposed method.\",\"PeriodicalId\":141108,\"journal\":{\"name\":\"2011 International Conference on Future Computer Sciences and Application\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Future Computer Sciences and Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFCSA.2011.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Future Computer Sciences and Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFCSA.2011.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SIFT Based Registration of Remotely-Sensed Imagery
this paper applies one kind of methods of automatic image registration, Scale Invariant Feature Transform(SIFT), into the region of remote sensing images. It has been found that SIFT can extract the features invariant to scale and rotation with specific key point descriptors as matching points for the registration of remote sensing images. Experimental results are discussed in the last part of this paper, and has confirmed the validity of the proposed method.
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