基于冗余关键点消除SARSIFT算法和MROGH描述符的图像配准

Zahra Hossein-Nejad, M. Nasri
{"title":"基于冗余关键点消除SARSIFT算法和MROGH描述符的图像配准","authors":"Zahra Hossein-Nejad, M. Nasri","doi":"10.1109/MVIP53647.2022.9738737","DOIUrl":null,"url":null,"abstract":"In this article, a new approach is suggested in remote-sensing images registration. In the suggested approach, first, the features extraction process is done based on proposed redundant keypoint elimination method synthetic aperture radar-SIFT (RKEM-SARSIFT). Second, creating descriptors is based on the Multi-Support Region Order-Based Gradient Histogram (MROGH) algorithm. Finally, matching process is done based on nearest neighbor distance ratio (NNDR) and transformation model is done based affine transform. The simulation results on several remote sensing image datasets affirm the suggested approach advantage in comparison with some other basic registration methods in terms of precision matching, SITMMR and SITMMC.","PeriodicalId":184716,"journal":{"name":"2022 International Conference on Machine Vision and Image Processing (MVIP)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Registration Based on Redundant Keypoint Elimination SARSIFT Algorithm and MROGH Descriptor\",\"authors\":\"Zahra Hossein-Nejad, M. Nasri\",\"doi\":\"10.1109/MVIP53647.2022.9738737\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, a new approach is suggested in remote-sensing images registration. In the suggested approach, first, the features extraction process is done based on proposed redundant keypoint elimination method synthetic aperture radar-SIFT (RKEM-SARSIFT). Second, creating descriptors is based on the Multi-Support Region Order-Based Gradient Histogram (MROGH) algorithm. Finally, matching process is done based on nearest neighbor distance ratio (NNDR) and transformation model is done based affine transform. The simulation results on several remote sensing image datasets affirm the suggested approach advantage in comparison with some other basic registration methods in terms of precision matching, SITMMR and SITMMC.\",\"PeriodicalId\":184716,\"journal\":{\"name\":\"2022 International Conference on Machine Vision and Image Processing (MVIP)\",\"volume\":\"88 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Machine Vision and Image Processing (MVIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MVIP53647.2022.9738737\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVIP53647.2022.9738737","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种新的遥感图像配准方法。在该方法中,首先,基于所提出的冗余关键点消除方法合成孔径雷达- sift (rkom - sarsift)进行特征提取;其次,基于多支持区域有序梯度直方图(MROGH)算法创建描述符。最后,基于最近邻距离比(NNDR)进行匹配处理,并基于仿射变换建立变换模型。在多个遥感影像数据集上的仿真结果证实了该方法在精度匹配、SITMMR和SITMMC方面优于其他基本配准方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Registration Based on Redundant Keypoint Elimination SARSIFT Algorithm and MROGH Descriptor
In this article, a new approach is suggested in remote-sensing images registration. In the suggested approach, first, the features extraction process is done based on proposed redundant keypoint elimination method synthetic aperture radar-SIFT (RKEM-SARSIFT). Second, creating descriptors is based on the Multi-Support Region Order-Based Gradient Histogram (MROGH) algorithm. Finally, matching process is done based on nearest neighbor distance ratio (NNDR) and transformation model is done based affine transform. The simulation results on several remote sensing image datasets affirm the suggested approach advantage in comparison with some other basic registration methods in terms of precision matching, SITMMR and SITMMC.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信