基于精细分割的SAR图像舰船目标几何结构特征提取

随着高分辨率星载合成孔径雷达（synthetic aperture radar，SAR）系统的研制和使用，利用SAR图像实现快速准确的舰船目标识别分类成为了海上目标侦察监视的重要手段.文中针对SAR舰船目标切片图像，提出一种基于精细分割的SAR图像舰船目标几何结构特征提取方法.首先，采用基于Radon变换的分割方法将舰船目标和成像干扰区域进行分离，对分离出的舰船目标切片进行阈值分割处理，并利用形态学手段处理分割图像，减小旁瓣影响，准确提取目标主区域；然后基于椭圆形状约束进行目标区域的细化分割，解决分割区域"毛刺"现象和区域断裂现象，得到舰船目标的最佳图像分割区域；最后，通过逼近目标区域获得其对应的最小外接矩形（minimum enclosing rectangle，MER），进而实现目标区域几何结构特征的精确提取.通过对获取的高分三号卫星SAR图像数据进行仿真实验，证明了本文方法提取舰船目标几何结构特征的高准确性和强稳定性，对海上舰船目标的识别与分类具有重要意义.

Geometric structure feature extraction of ship target in SAR imagebased on fine segmentation

With the development and application of the high resolution synthetic aperture radar (SAR) system, the rapid and accurate recognition and classification of ship targets based on SAR images has become an important means of maritime target reconnaissance and surveillance. A new method for geometric structure feature of ship targets in SAR images based on fine segmentation is proposed. Firstly, the Radon transform is adopted to separate ship targets with the "ghosting" or the "spider". The primary area of ship targets is obtained by the image threshold segmentation method, image processing based on the morphological method is adopted to inhibit the side lobe. Secondly, the target zone is refined based on the method of elliptical shape constraint, the "burr" phenomenon and the regional fracture phenomenon are well solved, and then the best image segmentation area for ship targets is acquired. Finally, the minimum circumscribed rectangle of target zone is obtained based on the successive approximation method to extract the geometric structure feature accurately. The experiments on the obtained GF-3 satellite SAR images demonstrate that our method proposed in this paper to extract the geometric structure feature of ship targets with high accuracy and strong stability, and it is significant for the identification and classification of ship targets at sea.