Superpixel-Level CFAR Detectors for Ship Detection in SAR Imagery

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Abstract

Synthetic aperture radar (SAR) is one of the most widely employed remote sensing modalities for large-scale monitoring of maritime activity. Ship detection in SAR images is a challenging task due to inherent speckle, discernible sea clutter, and the little exploitable shape information the targets present. Constant false alarm rate (CFAR) detectors, utilizing various sea clutter statistical models and thresholding schemes, are near ubiquitous in the literature. Very few of the proposed CFAR variants deviate from the classical CFAR topology; this letter proposes a modified topology, utilizing superpixels (SPs) in lieu of rectangular sliding windows to define CFAR guardbands and background. The aim is to achieve better target exclusion from the background band and reduced false detections. The performance of this modified SP-CFAR algorithm is demonstrated on TerraSAR-X and SENTINEL-1 images, achieving superior results in comparison to classical CFAR for various background distributions.
Original languageEnglish
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Early online date20 Jun 2018
DOIs
Publication statusE-pub ahead of print - 20 Jun 2018

Keywords

  • Constant false alarm rate (CFAR)
  • ship detection
  • superpixels (SPs)
  • synthetic aperture radar (SAR).

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