GLCM and Fuzzy Clustering for Ocean Features Classification

Authors:
  • RTRonghua Tao
    Ronghua Tao
  • JCJie Chen
    Jie Chen
  • BCBiao Chen
    Biao Chen
  • CLCuihua Liu
    Cuihua Liu

Abstract
Since Seasat lunched in 1978, much understanding has been gained on the potential of synthetic aperture radar (SAR) technology in oceanography. In this paper, the ocean features, i.e., internal waves, ocean fronts, present in SAR images are discussed. A new method for segmentation of SAR images is presented based on statistics of gray level co-occurrence matrix (GLCM) and the fuzzy C-Means clustering. The experimental results demonstrate its utility in the classification of various ocean features.

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