4.7 Article

Ship Detection for High-Resolution SAR Images Based on Feature Analysis

期刊

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 11, 期 1, 页码 119-123

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2013.2248118

关键词

Conventional constant false alarm rate (CFAR); feature analysis; high-resolution synthetic aperture radar (SAR); kernel density estimation; ship detection

资金

  1. National Natural Science Foundation of China [40871191]
  2. 863 Program [2011AA12Z139]

向作者/读者索取更多资源

High-resolution synthetic aperture radar (SAR) data have been widely used in marine environmental protection, marine environmental monitoring, and marine traffic management. Ship detection is one of the important parts of SAR data for marine applications. This letter focuses on the feature analysis of ships in high-resolution SAR images and proposes an improved optimizing algorithm for ship detection. A fast block detector is designed to extract sea clutter in a uniform local area, and then a constant false alarm rate detector is employed. Based on the kernel density estimation of ships, aspect ratio, and pixel points, ships are identified. TerraSAR-X and COSMO-SkyMed images are used to test our algorithm. The experimental results show that this algorithm can be implemented with time-saving, high-precision ship extraction, feature analysis, and detection.

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