• DocumentCode
    2318470
  • Title

    Synthetic aperture radar (SAR) image segmentation using a new modified fuzzy c-means algorithm

  • Author

    Chumsamrong, Warin ; Thitimajshima, Punya ; Rangsanseri, Yuttapong

  • Author_Institution
    Fac. of Eng., King Mongkut´´s Inst. of Technol., Bangkok, Thailand
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    624
  • Abstract
    Generally fuzzy c-means algorithm is one proved that very well suited for remote sensing image segmentation, exhibited sensitivity to the initial guess with regard to both speed and stability. But it also showed sensitivity to noise. This paper proposes a fully automatic technique to obtain image clusters. A modified fuzzy c-means classification algorithm is used to provide a fuzzy partition. This method is less sensitive to noise as it filters the image while clustering it, which is based on the consideration of the neighbors as factors the attract pixels into their cluster. The experimental results on JERS-1 synthetic aperture radar (SAR) image demonstrate its potential usefulness
  • Keywords
    geophysical signal processing; geophysical techniques; image segmentation; radar imaging; remote sensing by radar; synthetic aperture radar; terrain mapping; SAR; fuzzy c-means; fuzzy c-means algorithm; geophysical measurement technique; image clusters; image segmentation; land surface; radar imaging; radar remote sensing; synthetic aperture radar; terrain mapping; Clustering algorithms; Discrete wavelet transforms; Earth; Filters; Image segmentation; Multispectral imaging; Pixel; Remote sensing; Stability; Synthetic aperture radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-6359-0
  • Type

    conf

  • DOI
    10.1109/IGARSS.2000.861651
  • Filename
    861651