• DocumentCode
    1246983
  • Title

    Localized Radon transform-based detection of ship wakes in SAR images

  • Author

    Copeland, Anthony C. ; Ravichandran, Gopalan ; Trivedi, Mohan M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN, USA
  • Volume
    33
  • Issue
    1
  • fYear
    1995
  • fDate
    1/1/1995 12:00:00 AM
  • Firstpage
    35
  • Lastpage
    45
  • Abstract
    Presents a Radon transform-based approach to the detection of ship wakes in synthetic aperture radar (SAR) images. The key element of this technique is a localization of the Radon transform, whereby the intensity integration is performed over short line segments rather than across the entire image. A linear feature detection algorithm, which utilizes this localized Radon transform, is then developed. In this algorithm, referred to as the feature space line detector algorithm, the transform space is subjected to processing which serves to isolate and locate the response of linear features and suppresses the response of false alarms. This algorithm is tested on both synthetic images corrupted by various levels of Weibull multiplicative noise and on actual SAR images of ship wakes. The results of this testing demonstrate the algorithm´s robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions
  • Keywords
    Radon transforms; remote sensing by radar; ships; synthetic aperture radar; wakes; SAR images; Weibull multiplicative noise; feature space line detector algorithm; intensity integration; line segments; linear feature detection algorithm; localized Radon transform-based approach; ship wake detection; synthetic aperture radar; Computer vision; Detection algorithms; Detectors; Image segmentation; Marine vehicles; Noise level; Noise robustness; Radar detection; Synthetic aperture radar; Testing;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.368224
  • Filename
    368224