• DocumentCode
    3667285
  • Title

    Unsupervised hierarchical SAR image segmentation using lossy data compression

  • Author

    Gholamreza Akbarizadeh;Marjan Aleghafour

  • Author_Institution
    Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University, Ahvaz, Iran
  • fYear
    2015
  • fDate
    5/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a method called hierarchical unsupervised segmentation using lossy data compression for SAR images, where superpixels are used instead of pixels. In the present paper, merging the superpixels is dealt with by combining features such as edges, textures, and brightness. This procedure is done in two stages. The first stage is merging all superpixels until there is no distinct boundary between them. In second stage, merging superpixels is performed if lengths of data codes are minimized under definite distortion. The algorithm has been implemented on SAR images and it was observed that this algorithm has an appropriate accuracy and an acceptable speed.
  • Keywords
    "Image segmentation","Synthetic aperture radar","Merging","Feature extraction","Encoding","Data compression","Image edge detection"
  • Publisher
    ieee
  • Conference_Titel
    Information and Knowledge Technology (IKT), 2015 7th Conference on
  • Print_ISBN
    978-1-4673-7483-5
  • Type

    conf

  • DOI
    10.1109/IKT.2015.7288788
  • Filename
    7288788