• DocumentCode
    2571355
  • Title

    Recognition of remote sensing images in the three Gorges Reservoir Area by Fuzzy C-means Clustering algorithm based on Mahalanobis distance

  • Author

    Feng, Jing ; Rong, Che ; Juan, Wang

  • Author_Institution
    Xi´´an Commun. Inst., Xi´´an, China
  • Volume
    2
  • fYear
    2010
  • fDate
    28-31 Aug. 2010
  • Firstpage
    154
  • Lastpage
    156
  • Abstract
    Normal FCM (Fuzzy C-Means Clustering) algorithm is based on the Euclidean distance, which is the isotropic clustering method. In fact, the distribution of remote sensing data pixels don´t obey the isotropism or sphere distribution, and we can´t get good results in actual usage with normal FCM algorithm. So we choose FCM algorithm based on Mahalanobis distance, which is the appropriate distance measurement method for recognition and is selected according to the actual geographical distribution of remote sensing pixels. Then, we can recognize the land cover types of remote sensing images in the Three Gorges Reservoir Area with FCM algorithm based on Mahalanobis distance. The results show that this classification method can distinguish almost every pixel well, which have the same spectra but not same one, and we make the classified images a significant change with this method.
  • Keywords
    fuzzy set theory; geophysical image processing; image classification; matrix algebra; pattern clustering; remote sensing; Euclidean distance; Gorges reservoir area; Mahalanobis distance; fuzzy C means clustering algorithm; geographical distribution; image classification; image recognition; isotropic clustering method; land cover; remote sensing data pixel; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Fractals; Pixel; Remote sensing; Software; FCM; Mahalanobis distance; recognition of remote sensing images;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-8514-7
  • Type

    conf

  • DOI
    10.1109/IITA-GRS.2010.5601997
  • Filename
    5601997