• DocumentCode
    742335
  • Title

    PolSAR Ship Detection Based on Superpixel-Level Scattering Mechanism Distribution Features

  • Author

    Yinghua Wang ; Hongwei Liu

  • Author_Institution
    Nat. Lab. of Radar Signal Process., Xidian Univ., Xi´an, China
  • Volume
    12
  • Issue
    8
  • fYear
    2015
  • Firstpage
    1780
  • Lastpage
    1784
  • Abstract
    To improve the target detection performance under a low signal-to-clutter ratio, this letter presents a new polarimetric synthetic aperture radar (PolSAR) ship detector based on superpixel-level scattering mechanism (SM) distribution features. The proposed method is based on the observation that the SMs of targets and clutter have different distributions in the classical H/α plane. To make use of this difference in ship detection, multiscale superpixels are first generated for PolSAR images. Then, two features describing the SM distribution in the superpixel are proposed. Based on these features, a test statistic independent of the scattering intensity is finally defined. The performance improvement of the proposed method is verified using a synthetic data set and real PolSAR images obtained from a RADARSAT-2 data set.
  • Keywords
    object detection; radar clutter; radar detection; radar imaging; radar polarimetry; ships; statistical analysis; synthetic aperture radar; PolSAR imaging; PolSAR ship detection; RADARSAT-2 data set; SM; classical H-α plane; multiscale superpixel; polarimetric synthetic aperture radar; signal-to-clutter ratio; superpixel-level scattering mechanism distribution feature; target detection performance; Clutter; Detectors; Feature extraction; Marine vehicles; Scattering; Synthetic aperture radar; Thyristors; Polarimetric synthetic aperture radar (PolSAR); scattering mechanism (SM); ship detection; signal-to-clutter ratio (SCR); superpixel;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2015.2425873
  • Filename
    7107984