{"title":"一种无人机倾斜图像的亚像素配准方法","authors":"Chengyi Wang, Jingbo Chen, Dong-xu He","doi":"10.1109/IGARSS.2016.7730919","DOIUrl":null,"url":null,"abstract":"Since UAV oblique sequence images have large differences in perspective, it is difficult to achieve fully automatic, highly accurate registration using conventional image registration methods. To solve this problem, we present a sub-pixel image registration method based on ASIFT. Position of match points is corrected using the weighted least squares algorithm affine model (WLSM) one by one. Characteristics are selected and initial parameters estimation is also done through adaptive maximum cross-correlation algorithm (NCC). Experiments show that the proposed method is superior to conventional methods, such as SIFT and ASIFT, and this Method can achieve sub-pixel level registration precision.","PeriodicalId":179622,"journal":{"name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Sub-pixel registration method of UAV oblique images\",\"authors\":\"Chengyi Wang, Jingbo Chen, Dong-xu He\",\"doi\":\"10.1109/IGARSS.2016.7730919\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since UAV oblique sequence images have large differences in perspective, it is difficult to achieve fully automatic, highly accurate registration using conventional image registration methods. To solve this problem, we present a sub-pixel image registration method based on ASIFT. Position of match points is corrected using the weighted least squares algorithm affine model (WLSM) one by one. Characteristics are selected and initial parameters estimation is also done through adaptive maximum cross-correlation algorithm (NCC). Experiments show that the proposed method is superior to conventional methods, such as SIFT and ASIFT, and this Method can achieve sub-pixel level registration precision.\",\"PeriodicalId\":179622,\"journal\":{\"name\":\"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IGARSS.2016.7730919\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS.2016.7730919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Sub-pixel registration method of UAV oblique images
Since UAV oblique sequence images have large differences in perspective, it is difficult to achieve fully automatic, highly accurate registration using conventional image registration methods. To solve this problem, we present a sub-pixel image registration method based on ASIFT. Position of match points is corrected using the weighted least squares algorithm affine model (WLSM) one by one. Characteristics are selected and initial parameters estimation is also done through adaptive maximum cross-correlation algorithm (NCC). Experiments show that the proposed method is superior to conventional methods, such as SIFT and ASIFT, and this Method can achieve sub-pixel level registration precision.