一种喀斯特地貌无人机遥感影像的快速匹配方法
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摘要
针对喀斯特地貌地形起伏大、沟壑纵深、影像局部存在阴影,该地区无人机遥感影像匹配难度大,该文提出一种基于AKAZE特征和RANSAC算法的喀斯特地貌无人机遥感影像的快速匹配方法。该方法采用AKAZE特征检测算法提取喀斯特地貌无人机遥感影像的特征点,能够较为精简地描述出影像的特征,影像匹配时间缩短,匹配速度提高明显;由于预匹配存在错误点对,利用单应性矩阵的RANSAC算法进行精准匹配,剔除错误匹配点对,同时得到最优的单应性矩阵。实验结果表明,该方法的匹配耗时和匹配正确率较优于经典的SURF和BRISK算法,该匹配方法更适合于喀斯特地貌无人机遥感影像匹配。
In Karst Landform,in view of the large terrain,deep ravines and partial shadow,the UAV remote sensing image matching is difficult.In this paper,a fast matching method of UAV remote sensing images in Karst Landform based on AKAZE features and RANSAC algorithm is proposed.This method uses AKAZE feature detection algorithm of feature point extraction in Karst Landform of UAV remote sensing images,which can be more streamlined to describe feature of image,image matching time is shortened,the matching speed is obviously improved.There is an error point pair due to the prematching,so this paper will use RANSAC algorithm of homography matrix for accurate matching,eliminating the false matching points at the same time on, get the optimal homography matrix.Experimental results show that the matching time and matching rate of this method are better than those of classical SURF and BRISK algorithm.This matching method is more suitable for UAV remote sensing image matching in Karst Landform.
In Karst Landform,in view of the large terrain,deep ravines and partial shadow,the UAV remote sensing image matching is difficult.In this paper,a fast matching method of UAV remote sensing images in Karst Landform based on AKAZE features and RANSAC algorithm is proposed.This method uses AKAZE feature detection algorithm of feature point extraction in Karst Landform of UAV remote sensing images,which can be more streamlined to describe feature of image,image matching time is shortened,the matching speed is obviously improved.There is an error point pair due to the prematching,so this paper will use RANSAC algorithm of homography matrix for accurate matching,eliminating the false matching points at the same time on, get the optimal homography matrix.Experimental results show that the matching time and matching rate of this method are better than those of classical SURF and BRISK algorithm.This matching method is more suitable for UAV remote sensing image matching in Karst Landform.
引文
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[14]李鹏,武文波,王宗伟.基于非线性尺度空间的多源遥感影像匹配[J].测绘科学,2015,40(7):41-44.(LIPeng,WU Wenbo,WANG Zongwei.Multi-source remote sensing images matching based on nonlinear scale space[J].Science of Surveying and Mapping,2015,40(7):41-44.)
[15]覃兵,田军,查宇飞,等.利用二值描述符的实时目标跟踪算法[J].西安电子科技大学学报,2015,42(5):168-174.(QIN Bing,TIAN Jun,ZHA Yufei,et al.Realtime visual object tracking based on binary descriptors[J].Journal of Xidian University,2015,42(5):168-174.)
[2]张磊,彭力.结合SURF与Kalman滤波的CAMShift跟踪算法[J].电子测量与仪器学报,2017,31(3):389-394.(ZHANG Lei,PENG Li.Camshift tracking algorithm of combined with SURF and Kalman fliter[J].Journal of Electronic Measurement and Instrumention,2017,31(3):389-394.)
[3]赵明富,陈海军,宋涛,等.改进RANSAC-SIFT算法在图像匹配中的研究[J].激光杂志,2018,39(1):114-118.(ZHAO Mingfu,CHEN Haijun,SONG Tao,et al.Research on image matching based on improved RANSAC-SIFT algorithm[J].Laser Journal.2018,39(1):114-118.)
[4]罗楠,孙权森,耿蕾蕾,等.一种扩展SURF描述符及其在遥感图像配准中的应用[J].测绘学报,2013,42(3):383-388.(LUO Nan,SUN Quansen,GENG Leilei,et al.An extened SURF descriptor and its application in remote sensing images registration[J].Acta Geodaetica et Cartographica Sinica,2013,42(3):383-388.)
[5]牛俊伟,郝向阳,刘松林.一种改进的SIFT特征提取算法[J].测绘科学技术学报,2014,31(2):173-176.(NIU Junwei,HAO Xiangyang,LIU Songlin.An improved SIFT feature extraction algorithm[J].Journal of Geomatics Science and Technology,2014,31(2):173-176.)
[6]何林阳,刘晶红,李刚,等.改进BRISK特征的快速图像配准算法[J].红外与激光工程,2014,43(8):2722-2727.(HE Linyang,LIU Jinghong,LI Gang,et al.Fast image registration approach based on improved BRISK[J].Infrared and Laser Engineering,2014,43(8):2722-2727.)
[7]索效荣,齐苑辰.基于SIFT算法的无人机航空遥感影像匹配[J].测绘科学,2012,37(1):89-91.(SUOXiaorong,QI Yuanchen.Unmanned aerial vehicle image matching based on SIFT algorithm[J].Science of Surveying and Mapping,2012,37(1):89-91.)
[8]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an ef-ficient alternative to SIFT or SURF[C]//ICCV.Barcelona,Spain:[s.n.],2011:2564-2571.
[9]EDWARD R,REID P,TOM.Faster and better:a machine learning approach to corner detection[J].IEEETransactions on Pattern Analysis Machine Intelligence,2010,32(1):105-119.
[10]CALONDER M,LEPETIT V,FUA P.Brief:Binary robust independent elementary features[C]//ECCV.Crete,Greece:[s.n.],2010:778-792.
[11]卜范秋,宋伟东,王伟玺.一种针对近景影像的匹配算法[J].测绘科学,2013,38(6):143-146.(BU Fanqiu,SONG Weidong,WANG Weixi.A matching algorithm for close-range image[J].Science of Surveying and Mapping,2013,38(6):143-146.)
[12]ALCANTARILLA P F,BARTOLI A,DAVISON AJ.KAZE features[C]//ECCV.Florence,Italy:[s.n.],2012:214-227.
[13]ALCANTARILLA P F,NUEVO J,BARTOLI A.Fast explicit diffusion for accelerated features in nonlinear scale spaces[C]//BMVC.Bristol,UK:[s.n.],2013:1-11.
[14]李鹏,武文波,王宗伟.基于非线性尺度空间的多源遥感影像匹配[J].测绘科学,2015,40(7):41-44.(LIPeng,WU Wenbo,WANG Zongwei.Multi-source remote sensing images matching based on nonlinear scale space[J].Science of Surveying and Mapping,2015,40(7):41-44.)
[15]覃兵,田军,查宇飞,等.利用二值描述符的实时目标跟踪算法[J].西安电子科技大学学报,2015,42(5):168-174.(QIN Bing,TIAN Jun,ZHA Yufei,et al.Realtime visual object tracking based on binary descriptors[J].Journal of Xidian University,2015,42(5):168-174.)
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