电光与控制, 2018, 25 (4): 7, 网络出版: 2021-01-21   

基于频谱残差视觉显著计算的高分辨SAR图像舰船检测算法

A New Ship Target Detection Algorithm Based on Visual Salience Calculation of Spectral Residuals in High-Resolution SAR Images
作者单位
海军航空大信息融合研究所, 山东 烟台264001
摘要
分析了高分辨率SAR图像中海洋背景和舰船目标的特点,针对高分辨率SAR图像提出了一种两阶段舰船目标快速检测算法:第一阶段采用改进的频谱残差视觉显著计算模型快速获取视觉的感兴趣区域;第二阶段检测阶段,结合贝叶斯理论二元假设检验的思想,设计了一个局部最大后验概率分类器进行像素分类,经参数估计、判决准则完成显著区域内像素二分类以实现目标检测。实验采用典型的高分辨率SAR卫星Terra-SAR-X卫星数据进行仿真实验,结果表明所提算法具有良好的检测性能,也更加符合实际高分辨率图像舰船目标检测的应用需求。通过进一步实验与以往检测算法的对比得出结论,高分辨率SAR图像舰船目标检测方法在能够改善由斑点噪声和不均匀的海杂波背景对检测结果带来虚警的同时,检测速度也提高了25%~50%。
Abstract
The characteristics of the ocean background and the ship target in high-resolution SAR images were analyzed. A two-stage fast detection algorithm for ship target detection in high-resolution SAR images was proposed. At the first stage, an improved spectral residual visual salience calculation model was used to quickly obtain the visual region of interest. At the second stage of the detection, we designed a local maximum posteriori probability classifier for pixel classification based on Bayesian theory in binary hypothesis testing. After the parameter estimation, the criterion was completed and the pixels in the significant region were divided into two categories to achieve the target detection. Experiments were carried out using Terra-SAR-X and a large amount of military satellite data. The results showed that the proposed algorithm has good detection performance and is more in line with the application requirements of the actual high-resolution image ship target detection. By comparison with the conventional detection algorithm, it showed that: the algorithm proposed in this paper can not only reduce the false alarm caused by speckle noise, but also improve the detection speed by 25 percent to even 50 percent.

熊伟, 徐永力, 姚力波, 崔亚奇, 李岳峰. 基于频谱残差视觉显著计算的高分辨SAR图像舰船检测算法[J]. 电光与控制, 2018, 25(4): 7. XIONG Wei, XU Yongli, YAO Libo, CUI Yaqi, LI Yuefeng. A New Ship Target Detection Algorithm Based on Visual Salience Calculation of Spectral Residuals in High-Resolution SAR Images[J]. Electronics Optics & Control, 2018, 25(4): 7.

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