{"title":"Research on UAV Image Mosaic Based on Improved AKAZE Feature and VFC Algorithm","authors":"Q. Yan, Qianwen Li, Tongkang Zhang","doi":"10.1145/3449388.3449403","DOIUrl":null,"url":null,"abstract":"Aiming at the problem of low matching efficiency of traditional AKAZE algorithm, an improved algorithm is proposed that combines AKAZE and FREAK algorithms. First, AKAZE is used to extract feature points to ensure the accuracy of feature detection, and then the FREAK operator is used to calculate the descriptor, and then the VFC algorithm is used to perform accurate matching to improve the matching efficiency, and finally the weighted fusion algorithm is used to fuse the image. The research results show that compared with the traditional SIFT, the improved AKAZE algorithm improves the feature extraction time by about 1.11s, and the improved AKAZE algorithm in terms of computing descriptor efficiency increases the time by 1.32s than the SIFT and AKAZE algorithms, which can get higher The accuracy and matching results of the UAV realize rapid and seamless splicing of UAV images.","PeriodicalId":326682,"journal":{"name":"2021 6th International Conference on Multimedia and Image Processing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 6th International Conference on Multimedia and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3449388.3449403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Aiming at the problem of low matching efficiency of traditional AKAZE algorithm, an improved algorithm is proposed that combines AKAZE and FREAK algorithms. First, AKAZE is used to extract feature points to ensure the accuracy of feature detection, and then the FREAK operator is used to calculate the descriptor, and then the VFC algorithm is used to perform accurate matching to improve the matching efficiency, and finally the weighted fusion algorithm is used to fuse the image. The research results show that compared with the traditional SIFT, the improved AKAZE algorithm improves the feature extraction time by about 1.11s, and the improved AKAZE algorithm in terms of computing descriptor efficiency increases the time by 1.32s than the SIFT and AKAZE algorithms, which can get higher The accuracy and matching results of the UAV realize rapid and seamless splicing of UAV images.