基于归一化灰度Hough变换的SAR图像舰船尾迹检测算法

舰船尾迹检测作为近年来SAR图像海洋应用的一个重要方面而受到关注。目前大多数研究都是利用Radon变换作为数学工具，结果得到增强的是尾迹特征，而不是尾迹的端点。从提取尾迹的端点坐标出发，在传统Hough变换算法基础上进行改进，提出了基于归一化灰度Hough变换的SAR图像舰船尾迹检测算法，并推导出尾迹端点反演算法，同时自动提取舰船的航速，取得了较好的实验结果。

Ship Wake Detection Algorithm in SAR Image Based on Normalized Grey Level Hough Transform

As one of the important applications in Synthetic Aperture Radar(SAR) images, ship wake detection has been received considerable attentions in the area of marine remote sensing. Recently, most researches on ship wake detection depend on the mathematical tool of Radon transform. However, the result of Radon transform is the image with which wake character being enhanced but not the end points of the wakes. In order to calculate the ship's velocity, the aim of the research is to detect the end points of ship wakes. Found on the improvement of the conventional Hough transform, a normalized Hough transform algorithm based on grey level is proposed. It can make the detection result independent of the noise and the different lengths of different lines using the normalization technology. The steps of algorithm are presented. The expression of the wake's end points is derived. On the other hand, the calculation algorithm of ship's moving velocity is presented. Both the time complexity and space complexity of the normalized Hough transform and the conventional Hough transform are analyzed respectively. This algorithm is applied to the ship wake detection in SAR image. The experiments obtained good results and can extract ship's velocity automatically.