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A Novel Ship Segmentation Method Based on Kurtosis Test in Complex-Valued SAR Imagery

Traditional ship segmentation methods in synthetic aperture radar (SAR) imagery are mainly based on the intensity/amplitude information. They cannot take fully advantage of the complex information in SAR imagery. This paper proposes a novel ship segmentation method based on kurtosis test in the complex-valued SAR imagery. It can take benefit of the complex information of the SAR imagery. The segmentation rationale is that sea clutter usually obey a Gaussian distribution while ship targets usually obey a sup-Gaussian distribution. Thus, their kurtosis can be different. Kurtosis is invariant with respect to location shift and positive scale changes. It follows that kurtosis of sea clutter remains approximately constant while the amplitude decreases with the incidence angle increasing. Preliminary experimental results based on Gaofen-3 and Sentinel-1 data show that the proposed method can achieve good performance.