ABSTRACT

This paper proposes a new ship detection algorithm via saliency analysis on multiscale superpixels. First, Synthetic Aperture Radar (SAR) imagery is over-segmented into many homogenous regions, called superpixels. In contrast to prior work, these superpixels are generated with various scales to handle size variation of ships in the SAR imagery. At each scale, local contrast and ship geometrical characteristics are considered to enhance the saliency of ship pixels. Then, the final saliency map is computed by integrating saliency values of all scales. Experimental results on two real SAR images demonstrate the efficiency of the proposed algorithm.

摘要

本文通过对多尺度超像素的显着性分析提出了一种新的船舶检测算法。首先，合成孔径雷达 (SAR) 图像被过度分割成许多同质区域，称为超像素。与之前的工作相比，这些超像素以各种比例生成，以处理 SAR 图像中船舶的尺寸变化。在每个尺度上，考虑局部对比度和船舶几何特征以增强船舶像素的显着性。然后，通过整合所有尺度的显着值来计算最终的显着图。两幅真实 SAR 图像的实验结果证明了所提算法的有效性。