• DocumentCode
    21340
  • Title

    Multilayer CFAR Detection of Ship Targets in Very High Resolution SAR Images

  • Author

    Biao Hou ; Xingzhong Chen ; Licheng Jiao

  • Author_Institution
    Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi´an, China
  • Volume
    12
  • Issue
    4
  • fYear
    2015
  • fDate
    Apr-15
  • Firstpage
    811
  • Lastpage
    815
  • Abstract
    This letter proposes a new ship target detection method for very high resolution (VHR) synthetic aperture radar (SAR) images based on multilayer constant false alarm rate (CFAR). First, combined with log-normal distribution, a multilayer CFAR method is designed to overcome the holes and the fracture in the traditional detected results. This method can retain more details of ships and takes much less time than the traditional CFAR method for VHR SAR images. Second, based on a priori knowledge of ships, we use the sliding window to remove the false alarm targets. Finally, In order to measure the size and shape of a ship, we extract the outline of a ship and fill it by a level set method. Experimental results, carried out on real SAR images, demonstrate that the proposed approach outperforms the previous one in terms of the detection ratio of pixels instead of the number of ships.
  • Keywords
    image resolution; image sensors; log normal distribution; object detection; radar detection; radar imaging; shape measurement; ships; size measurement; synthetic aperture radar; VHR synthetic aperture radar imaging; fracture; log-normal distribution; multilayer CFAR detection; multilayer constant false alarm rate detection; shape measurement; ship target detection method; size measurement; sliding window removal; very high resolution SAR imaging; Clutter; Detectors; Image resolution; Marine vehicles; Nonhomogeneous media; Scattering; Synthetic aperture radar; Multilayer constant false alarm rate (multilayer CFAR); ship detection; sliding window; synthetic aperture radar (SAR);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2362955
  • Filename
    6942175