| Technology and Methodology |
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Automatic registration method for remote sensing images based on improved ORB algorithm |
| ZHANG Yunsheng, ZOU Zhengrong |
| School of Geosciences and Info-Physics, Central South University, Changsha 410083, China |
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Abstract Aiming at reliable registration of remote sensing images,the authors present in this paper a remote sensing image registration method based on improved ORB (oriented brief) algorithm. The proposed method mainly includes three stages:The first stage is feature matching, the improved ORB algorithm is used to detect features and build descriptors,and the descriptors are matched to obtain initial control points. The second stage is to employ RANSAC (random sample consensus) processing via transformation parameters estimation to remove possible wrong matching points. The third stage is to rectify the image based on the transformation parameters calculated by the least square method. The proposed method is evaluated based on two sets of optical and SAR remote sensing images,and is compared with the registration methods based on SIFT and SURF algorithm. The results show that the method proposed in this paper can provide the same accurate remote sensing image registration result as or even the higher result than the methods based on SIFT and SURF algorithm,and can obtain improved efficiency.
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| Keywords
wet delay
DEM
Shuping landslide
best-fit-function models
deformation field
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Issue Date: 03 July 2013
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| [1] Kern J P,Pattichis M S.Robust multispectral image registration using mutual-information models[J].IEEE Transactions on Geoscience and Remote Sensing,2007,45(5):1494-1505.[2] 韦春桃,吴平,张祖勋,等.一种改进的相位相关的影像配准方法[J].测绘通报,2011(4):19-22. Wei C T,Wu P,Zhang Z X,et al.An image matching algorithm based on improved log-polar image transform[J].Bulletin of Surveying and Mapping,2011(4):19-22.[3] Liu X Z,Tian Z,Chai C Y,et al.Multiscale registration of remote sensing image using robust SIFT features in steerable-domain[J].The Egyptian J Remote Sensing and Space Sci,2011,14(2):63-72.[4] 李晓明,郑链,胡占义.基于SIFT特征的遥感影像自动配准[J].遥感学报,2006,10(6):885-892. Li X M,Zhen L,Hu Z Y.SIFT based automatic registration of remotely-sensed imagery[J].Journal of Remote Sensing,2006,10(6):885-892.[5] 林晓帆,林立文,邓涛.基于SURF描述子的遥感影像配准[J].计算机工程,2010,36(12):216-218. Lin X F,Lin L W,Deng T.Remote sensing image registration based on SURF gescriptor[J].Computer Engineering,2010,36(12):216-218.[6] Calonder M,Lepetit V,Ozuysal M,et al.BRIEF:Computing a local binary descriptor very fast[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(6):1281-1298.[7] Rublee E,Rabaud V,Konolige K,et al.ORB:An efficient alternative to SIFT or SURF［C］//2011 International Conference on Computer Vision,Barcelona,Spain,2011:2564-2571[8] Rosten E,Drummond T.Machine learning for high-speed corner detection［C］//Lecture Notes in Computer Science,2006,3951:430-443.[9] 李慧,蔺启忠,刘庆杰.基于FAST和SURF的遥感图像自动配准方法[J].国土资源遥感,2012,24(2):28-33. Li H,Lin Q Z,Liu Q J.An automatic registration method of remote sensing imagery based on FAST corner and SURF descriptor[J].Remote Sensing for Land and Resources,2012,24(2):28-33.[10] Fischer M A,Bolles R C.Random sample consensus:A paradigm for model fitting with applications to image analysis and automated cartography[J].Communications of the ACM,1981,24(6):381-395.[11] Marius M,Lowe D G.Fast approximate nearest neighbors with automatic algorithm configuration［C］//International Conference on Computer Vision Theory and Applications,Lisboa,Portugal,2009:331-340.[12] Lowe D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.[13] Bay H,Ess A,Tuytelaars T,et al.Speeded-up robust features(SURF)[J].Computer Vision and Image Understanding,2008,110(3):346-359. |
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2013,
Vol. 25
