• DocumentCode
    226410
  • Title

    The SAR image segmentation superpixel-based with optimized spatial information

  • Author

    Xiaolin Tian ; Licheng Jiao ; Long Yi ; Xiaohua Zhang

  • Author_Institution
    Int. Res. Center for Intell. Perception & Comput., Xidian Univ., Xi´an, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    171
  • Lastpage
    177
  • Abstract
    In this paper, we propose a method of image segmentation, which is based on superpixel and optimized spatial feature. In this paper, the superpixels are taken into account, which can reduce computational burden, and the result of over-segmentation can also be benefit for segmentation results. The main idea of this paper is based on the conventional fuzzy c-means (FCM). The conventional FCM has a better performance. However, it is sensitive to noise. In order to overcome this shortage, we incorporate spatial information of superpixels into the conventional FCM. In order to obtain the better performance, influential degree of spatial information is applied to the conventional FCM to improve segmentation performance Experimental results show that the proposed method achieves excellent performance.
  • Keywords
    feature extraction; fuzzy set theory; geophysical image processing; image resolution; image segmentation; pattern clustering; radar imaging; synthetic aperture radar; FCM; SAR image segmentation superpixel; fuzzy c-means; optimized spatial feature; optimized spatial information; synthetic aperture radar images; Classification algorithms; Clustering algorithms; Feature extraction; Image segmentation; Linear programming; Noise; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891528
  • Filename
    6891528