异源多分辨率卫星影像匹配算法研究
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摘要
以异源多分辨率遥感卫星影像为研究对象,对影像特征提取、特征描述、特征匹配及匹配提纯算法进行了较为深入的研究;并将不同的特征提取与匹配算法进行组合,通过试验对比得出了各种算法的适用性。在此基础上,设计了一套面向异源多分辨率卫星影像的匹配流程。
In this paper,the image feature extraction,feature description,feature matching and the matching purification algorithm are studied by taking the satellite image of heterogeneous and multi-resolution remote sensing as the research object. Different feature extraction and matching algorithms are combined and the applicability of each algorithm is obtained through experimental comparison.Based on this,a set of matching process for multi-resolution satellite images is designed.
In this paper,the image feature extraction,feature description,feature matching and the matching purification algorithm are studied by taking the satellite image of heterogeneous and multi-resolution remote sensing as the research object. Different feature extraction and matching algorithms are combined and the applicability of each algorithm is obtained through experimental comparison.Based on this,a set of matching process for multi-resolution satellite images is designed.
引文
[1]李德仁,张良培,夏桂松.遥感大数据自动分析与数据挖掘[J].测绘学报,2014,43(12):1211-1216.
[2]张祖勋,陶鹏杰.谈大数据时代的“云控制”摄影测量[J].测绘学报,2017,46(10):1238-1248.
[3]FISCHLER 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.
[4]KE Y,SUKTHANKAR R.PCA-SIFT:a more distinctive representation for local image descriptors[J].Computer Vision and Pattern Recognition,2004,2(2):506-513.
[5]BAY H,TUYTELAARS T,GOOL L V.SURF:speeded up robust features[J].Computer Vision and Image Understanding,2006,110(3):404-417.
[6]ALCANTARILLA P F,BARTOLI A,NVEVO J.KAZE features[C]∥Proceedings of European Conference on Computer Vision.Berlin,Heidelberg:Springer,2012.
[7]ALCANTARILLA P F,NUEVO J,BARTOLI A.Fast explicit diffusion for accelerated features in nonlinear scale spaces[C]∥Proceedings of British Machine Vision Conference.Bristol:[s.n.],2013.
[8]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an efficient alternative to SIFT or SURF[C]∥Proceedings of IEEE International Conference on Computer Vision.[S.l.]:IEEE,2012.
[9]许允喜,陈方.局部图像描述符最新研究进展[J].中国图象图形学报,2015,20(9):1133-1150.
[10]TRAPPEY A J C,HSU F,TRAPPEY C V,et al.Development of a patent document classification and search platform using a backplatform network[J].Expert Systems with Applications,2006,31(4):755-765.
[11]董杨.大数据影像稀疏三维重建理论与方法研究[D].郑州:信息工程大学,2017.
[12]CHUM O,MATAS J.Optimal randomized RANSAC[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2008,30(8):1472-1482.
[13]董杨,范大昭,纪松,等.主成分分析的匹配点对提纯方法[J].测绘学报,2017,46(2):228-236.
[14]王亚伟,许廷发,王吉晖.改进的匹配点提纯算法mRANSAC[J].东南大学学报(自然科学版),2013,43(S1):163-167.
[15]纪松,张永生,范大昭,等.基于特征点引导的多视影像择优匹配方法[J].武汉大学学报(信息科学版),2018,43(1):37-45.
[2]张祖勋,陶鹏杰.谈大数据时代的“云控制”摄影测量[J].测绘学报,2017,46(10):1238-1248.
[3]FISCHLER 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.
[4]KE Y,SUKTHANKAR R.PCA-SIFT:a more distinctive representation for local image descriptors[J].Computer Vision and Pattern Recognition,2004,2(2):506-513.
[5]BAY H,TUYTELAARS T,GOOL L V.SURF:speeded up robust features[J].Computer Vision and Image Understanding,2006,110(3):404-417.
[6]ALCANTARILLA P F,BARTOLI A,NVEVO J.KAZE features[C]∥Proceedings of European Conference on Computer Vision.Berlin,Heidelberg:Springer,2012.
[7]ALCANTARILLA P F,NUEVO J,BARTOLI A.Fast explicit diffusion for accelerated features in nonlinear scale spaces[C]∥Proceedings of British Machine Vision Conference.Bristol:[s.n.],2013.
[8]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an efficient alternative to SIFT or SURF[C]∥Proceedings of IEEE International Conference on Computer Vision.[S.l.]:IEEE,2012.
[9]许允喜,陈方.局部图像描述符最新研究进展[J].中国图象图形学报,2015,20(9):1133-1150.
[10]TRAPPEY A J C,HSU F,TRAPPEY C V,et al.Development of a patent document classification and search platform using a backplatform network[J].Expert Systems with Applications,2006,31(4):755-765.
[11]董杨.大数据影像稀疏三维重建理论与方法研究[D].郑州:信息工程大学,2017.
[12]CHUM O,MATAS J.Optimal randomized RANSAC[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2008,30(8):1472-1482.
[13]董杨,范大昭,纪松,等.主成分分析的匹配点对提纯方法[J].测绘学报,2017,46(2):228-236.
[14]王亚伟,许廷发,王吉晖.改进的匹配点提纯算法mRANSAC[J].东南大学学报(自然科学版),2013,43(S1):163-167.
[15]纪松,张永生,范大昭,等.基于特征点引导的多视影像择优匹配方法[J].武汉大学学报(信息科学版),2018,43(1):37-45.