提出了一种基于复合参数分布的SAR图像船只检测模型。模型使用Pearson分布系统模拟SAR图像海洋背景散射分布, Pearson分布系统由4种参数分布组成, 包括Pearson I分布(g)、Ⅲ分布、Ⅳ分布(反g)和Ⅵ分布。模型采用基于β平面的分布选择器确定采用哪种分布来拟合SAR图像海面后向散射分布, 同时利用4种分布, 结合CFAR技术, 建立CFAR方程, 通过解算方程得到检测阈值, 利用阈值进行SAR图像船只检测。通过图像试验验证表明, 该模型检测效果良好, 具有一定的实用价值。

In this paper, we propose a new ship detection model based on SAR imagery. The model uses the Pearson distribution system to simulate the backscattering distribution of ocean surface on SAR imagery. In the Pearson distribution system, four distributions including the Pearson distributions of typeⅠ(γ), Ⅲ, Ⅳ(Inverse γ) and Ⅵ are employed. Using these four distributions, we build a CFAR equation. A distribution selection machine based on β plane is used to select which distribution is adopted to specified SAR imagery. We can get four equations and the threshold of gray level. Then, using the threshold, the model can find ships from SAR images. Some tests show this model working well.