• DocumentCode
    3346846
  • Title

    On the use of higher order statistics in SAS imagery [synthetic aperture sonar]

  • Author

    Maussang, F. ; Chanussot, J. ; Hétet, A.

  • Author_Institution
    Lab. des Images et des Signaux, Domaine Univ., Saint-Martin-D´´Heres, France
  • Volume
    5
  • fYear
    2004
  • fDate
    17-21 May 2004
  • Abstract
    Synthetic aperture sonar (SAS) imagery is largely used in detection, location and classification of underwater mines laying on or buried in the sea bed. This paper proposes a detection method using higher order statistics (HOS) on SAS images. The proposed method can be divided into two steps. Firstly, the HOS (skewness and kurtosis) are locally estimated using a square sliding computation window. In a second step, the results are focused by a correlation process. This enables the precise location of the objects. This method is tested on real SAS data containing both underwater mines laying on the sea bed and buried objects.
  • Keywords
    buried object detection; correlation methods; higher order statistics; image classification; object detection; sonar imaging; synthetic aperture sonar; HOS; SAS imagery; buried objects; correlation process; higher order statistics; kurtosis; mine classification; mine detection; mine location; sea bed buried mines; sea bed imagery; sea bed laying mines; skewness; square sliding computation window; synthetic aperture sonar; underwater mines; Buried object detection; Dissolved gas analysis; Focusing; Gaussian distribution; Higher order statistics; Noise level; Sea measurements; Synthetic aperture sonar; Testing; Underwater tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-8484-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2004.1327099
  • Filename
    1327099