• DocumentCode
    3690785
  • Title

    GGSOR: A Gaussian-Gamma-Shaped bi-windows based descriptor for optical and SAR images matching

  • Author

    Min Chen;Qing Zhu;Jun Zhu

  • Author_Institution
    Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, P. R. China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    3683
  • Lastpage
    3686
  • Abstract
    A matching method for optical and synthetic aperture radar (SAR) images, robust to speckle noise, is presented. Firstly, a coarse correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed by combining the Gaussian-Gamma-Shaped bi-windows based gradient operator and the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing. The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.
  • Keywords
    "Synthetic aperture radar","Optical imaging","Adaptive optics","Optical sensors","Robustness","Image matching","Feature extraction"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7326622
  • Filename
    7326622