ELCVIA Electronic Letters on Computer Vision and Image Analysis (May 2013)

An Automatic Ship Detection Method Based on Local Gray-Level Gathering Characteristics in SAR Imagery

  • Xiaolong Wang,
  • Cuixia Chen

DOI
https://doi.org/10.5565/rev/elcvia.528
Journal volume & issue
Vol. 12, no. 1

Abstract

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This paper proposes an automatic ship detection method based on gray-level gathering characteristics of synthetic aperture radar (SAR) imagery. The method does not require any prior knowledge about ships and background observation. It uses a novel local gray-level gathering degree (LGGD) to characterize the spatial intensity distribution of SAR image, and then an adaptive-like LGGD thresholding and filtering scheme to detect ship targets. Experiments on real SAR images with varying sea clutter backgrounds and multiple target situations have been conducted. The performance analysis confirms that the proposed method works well in various circumstances with high detection rate, fast detection speed and perfect shape preservation.

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