• DocumentCode
    508408
  • Title

    Registration of Remote Sensing Images Based on the Relevance Vector Machine

  • Author

    Wang, Xiaofei ; Zhang, Junping ; Zhang, Ye

  • Author_Institution
    Dept. of Inf. Eng., Harbin Inst. of Technol., Harbin, China
  • Volume
    1
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    547
  • Lastpage
    551
  • Abstract
    Remote sensing has become a technique of indispensable importance for us to acquire the information on the ground. In the process of imaging, geometric distortion occurs due to several factors, which causes many difficulties when using those remote images for change detection, information fusion, resolution enhancement and so on. So the image registration is necessary. Aiming at the distortion type for the selection of geometric transformation model in the registration process, a relevance vector machine (RVM) based geometric transformation model is given, which will solve the problem of nonlinear geometric distortion efficiently as well as avoiding the shortcomings in the traditional model. Experiments have been realized this method.
  • Keywords
    computational geometry; image registration; learning (artificial intelligence); remote sensing; geometric transformation model; image registration; nonlinear geometric distortion; relevance vector machine; remote sensing; Distortion measurement; Educational institutions; Geometry; Image registration; Image resolution; Nonlinear distortion; Pixel; Polynomials; Remote sensing; Solid modeling; Registration; Remote Sensing Image; relevance vector machine (RVM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.583
  • Filename
    5367192