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一种结合拓扑信息和SIFT特征的多源遥感影像自动匹配方法 被引量:7

A Multi-sensor Remote Sensing Image Automatic Matching Method Based on Topological Information and SIFT Features
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摘要 基于单一特征的匹配办法在多源遥感影像匹配中往往不适用的问题,提出了一种结合拓扑信息和SIFT特征的自动多源遥感影像匹配方法。该方法首先在两幅影像中使用SIFT算法在尺度空间上提取特征向量,其次对这些特征点使用最近邻提取1:N的多个可能的匹配点对,然后结合位置信息和拓扑信息对这些可能的匹配点对进行剔除,并使用RANSAC方法剔除粗差,最终得到同名匹配点。试验结果表明,相比于计算机视觉领域常用的SIFT算法,本文方法可有效地提高匹配正确率,并获得更多正确的同名点。 Based on the question of matching method of single feature matching in multi-source remote sensing images are often not ideal, a matching method for combination of topology information and SIFT automatic feature of multi-source remote sensing image is proposed in this paper. The method first in two images using the SIFT algorithm in scale space to extract feature vectors, then these feature points using the nearest neighbor the extraction of 1 : N multiple possible matching points. Secondly, the matching points are eliminated by the combination of location information and topological information, and the double edge matching strategy and the RANSAC method are used to eliminate the coarse tea. The experimental results show that compared with the SIFT algorithm commonly used in the field of computer vision, the proposed method can effectively improve the matching accuracy and obtain more correct points of the same name.
出处 《测绘通报》 CSCD 北大核心 2017年第10期115-119,共5页 Bulletin of Surveying and Mapping
关键词 多源影像配准 拓扑信息 SIFT multi-sensor image registration topological information SIFT
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  • 1张力,张继贤.基于多基线影像匹配的高分辨率遥感影像DEM自动生成[J].测绘科学,2008,33(S2):35-39. 被引量:23
  • 2张继贤,李国胜,曾钰.多源遥感影像高精度自动配准的方法研究[J].遥感学报,2005,9(1):73-77. 被引量:45
  • 3Li H, Manjunath B S, Mitra S K. A contour-based approach to multisensor image registration. IEEE Transactions on Image Processing, 1995, 4(3): 320-334.
  • 4Dare P, Dowman I. An improved model for automatic feature-based registration of SAR and SPOT images. ISPRS Journal of Photogrammetry and Remote Sensing. 2001, 56(1): 13-28.
  • 5Hong T D, Schowengerdt R A. Automated precise registration of radar and optical satellite images. In: Proceedings of SPIE Conference on Applications of Digital Image Processing. San Diego, USA: IEEE, 2003. 88-96.
  • 6Shekhar C, Govindu V, Chellappa R. Multisensor image registration by feature consensus. Pattern Recognition, 1999, 32(1): 39--52.
  • 7Middelmann W, Pepelka V, Thoennessen U. Registration of multiaspect InSAR images. In: Proceedings of SPIE Conference on Algorithms for Synthetic Aperture Radar Imagery. Orlando, USA: SPIE, 2003, 98-109.
  • 8Yao J C, Kian L G. A refined algorithm for multisensor image registration based on pixel migration. IEEE Transactions on Image Processing, 2006, 15(7): 1839-1847.
  • 9Keller Y, Averbuch A. Multisensor image registration via implicit similarity. IEEE Transactions on Pattern Analysis and Mt~chine Intelligence, 2006, 28(5): 794-801.
  • 10Kruger W. Robust and efficient map-to-image registration with line segments. Machine Vision and Applications, 2001, 13(1): 38-50.

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