• DocumentCode
    2714313
  • Title

    Automatic registration between remote sensing image and vector data based on line features

  • Author

    Liu, Zhiqing ; Zhang, Baoming ; Li, Pengcheng ; Guo, Haitao ; Han, Jinning

  • Author_Institution
    Inst. of Surveying & Mapping, Inf. Eng. Univ., Zhengzhou, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In recent years, registration between the remote sensing image and vector data has seen its increasing usage in photogrammetry-related applications. Many researchers select higher-level primitives instead of traditional control points since the disadvantages of point features. This paper has proposed an automatic registration approach based on line features, which is insensitive to rotational and scale transformation. In this approach, the similarity measure is established according to the distance between conjugate entities in the same reference coordinate system. The collinearity equation is chosen as the transformation function. A modified Hough Transform is adopted to simultaneously estimate the exterior orientation parameters and obtain matching results. The automatic registration between the remote sensing image and vector data is achieved as well as the exterior orientation of the remote sensing image. Experimental results proved the reliability and feasibility of this approach.
  • Keywords
    Hough transforms; geophysical image processing; image matching; image registration; photogrammetry; remote sensing; Hough transform; automatic registration approach; collinearity equation; exterior orientation parameter; higher level primitive; line feature; photogrammetry related application; remote sensing image; transformation function; Accuracy; Approximation methods; Arrays; Equations; Feature extraction; Mathematical model; Remote sensing; line features; registration; search strategy; similarity measure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5981167
  • Filename
    5981167