최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기The Photogrammetric record, v.30 no.151, 2015년, pp.263 - 278
Li, Na , Huang, Xianfeng , Zhang, Fan , Li, Deren
AbstractImage registration is a prerequisite for multisource data fusion. In this paper the problem of registering aerial images with lidar point clouds in desert areas is addressed. Compared with urban areas, registration in desert regions is difficult due to the lack of man‐made features whi...
RésuméLe recalage d'images est un préalable à la fusion de données multisource. Cet article aborde le problème du recalage entre des images aériennes et des nuages de points lidar en région désertique. Le recalage est plus difficile dans les déserts qu'en milieu urbain en raison de la rareté des objets artificiels que les méthodes traditionnelles ont coutume d'utiliser. Cependant les crêtes de sable peuvent servir de primitives pour le recalage. On extrait d'abord l'information de ces crêtes de sable à la fois dans l'image aérienne et dans le nuage de points lidar. L'approche ICP (recherche itérative du point le plus proche) est ensuite étendue à un algorithme «?perspective‐ICP?» utilisant une transformation perspective et capable de recaler les données entre elles à partir de l'appariement des crêtes de sable. Les cas atypiques sont pris en compte par l'adoption d'une stratégie de pondération adaptative. Une expérimentation a été menée avec des données sur Dunhuang dans le désert de Gobi (Chine), et les résultats montrent que la méthode conduit à un recalage efficace et fiable en région désertique.
Armenakis , C. , Gao , Y. and Sohn , G. , 2013 . Co‐registration of aerial photogrammetric and LiDAR point clouds in urban environments using automatic plane correspondence . Applied Geomatics , 5 ( 2 ): 155 – 166 .
Baez , S. , Collins , S. L. , Pockman , W. T. , Johnson , J. E. and Small , E. E. , 2013 . Effects of experimental rainfall manipulations on Chihuahuan Desert grassland and shrubland plant communities . Oecologia , 172 ( 4 ): 1117 – 1127 .
Besl , P. J. and McKay , H. D. , 1992 . A method for registration of 3–D shapes . IEEE Transactions on Pattern Analysis and Machine Intelligence , 14 ( 2 ): 239 – 256 .
Canny , J. , 1986 . A computational approach to edge detection . IEEE Transactions on Pattern Analysis and Machine Intelligence , 8 ( 6 ): 679 – 698 .
Gonzalez , R. C. , Woods , R. E. and Eddins , S. L. , 2009 . Digital image processing using MATLAB . Second edition . Gatesmark Publishing , Knoxville, Tennessee, USA . 827 pages.
Gressin , A. , Mallet , C. and David , N. , 2012 . Improving 3D Lidar point cloud registration using optimal neighborhood knowledge . ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences , 1–3 : 111 – 116 .
Gruen , A. and Huang , T. S. (Eds.), 2001 . Calibration and orientation of cameras in computer vision . Springer , Berlin, Germany . 236 pages.
Guo , Z. and Hall , R. W. , 1989 . Parallel thinning with two‐subiteration algorithms . Communications of the ACM , 32 ( 3 ): 359 – 373 .
Habib , A. , Ghanma , M. and Mitishita , E. , 2004 . Co‐registration of photogrammetric and lidar data: methodology and case study . Revista Brasileira de Cartografia , 56 ( 1 ): 1 – 13 .
Habib , A. , Ghanma , M. , Morgan , M. and Al‐Ruzouq , R. , 2005 . Photogrammetric and lidar data registration using linear features . Photogrammetric Engineering & Remote Sensing , 71 ( 6 ): 699 – 707 .
Huang , X. , 2013 . Building reconstruction from airborne laser scanning data . Geo‐spatial Information Science , 16 ( 1 ): 35 – 44 .
Li , N. , Huang , X. , Zhang , F. and Wang , L. , 2013 . Registration of aerial imagery and Lidar data in desert areas using the centroids of bushes as control information . Photogrammetric Engineering & Remote Sensing , 79 ( 8 ): 743 – 752 .
Lindeberg , T. , 1998 . Edge detection and ridge detection with automatic scale selection . International Journal of Computer Vision , 30 ( 2 ): 117 – 156 .
Mastin , A. , Kepner , J. and Fisher , J. , 2009 . Automatic registration of LIDAR and optical images of urban scenes. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , Miami, Florida, USA. 2639 – 2646 .
Mitishita , E. , Habib , A. , Centeno , J. , Machado , A. , Lay , J. and Wong , C. , 2008 . Photogrammetric and lidar data integration using the centroid of a rectangular roof as a control point . Photogrammetric Record , 23 ( 121 ): 19 – 35 .
Rusinkiewicz , S. and Levoy , M. , 2001 . Efficient variants of the ICP algorithm. International Conference on 3‐D Digital Imaging and Modeling , Quebec City, Quebec, Canada. Pages 145–152.
Singhvi , A. , Williams , M. A. J. , Rajaguru , S. N. , Misra , V. N. , Chawla , S. , Stokes , S. , Chauhan , N. , Francis , T. , Ganjoo , R. K. and Humphreys , G. S. , 2010 . A ~200 ka record of climatic change and dune activity in the Thar Desert, India . Quaternary Science Reviews , 29 ( 23–24 ): 3095 – 3105 .
Soille , P. , 2004 . Morphological image analysis: principles and applications . Second edition . Springer , Berlin, Germany . 391 pages.
Vassilaki , D. I. , Ioannidis , C. C. and Stamos , A. A. , 2012 . Automatic ICP‐based global matching of free‐form linear features . Photogrammetric Record , 27 ( 139 ): 311 – 329 .
Wang , R. , Bach , J. , Macfarlane , J. and Ferrie , F. P. , 2012a . A new upsampling method for mobile LiDAR data. IEEE Workshop on Applications of Computer Vision (WACV) , Breckenridge, Colorado, USA. Pages 17–24.
Wang , R. , Ferrie , F. P. and Macfarlane , J. , 2012b . Automatic registration of mobile LiDAR and spherical panoramas. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , Providence, Rhode Island, USA. Pages 33–40.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.