摘要
提出了一种基于正则化方法的SAR图像边缘检测算法,并用MSTAR(moving and stationary target acquisitions and recognition)数据进行大量的仿真实验。实验表明,与经典的边缘检测方法相比,该方法能保持图像的细节特征,较好地解决了边缘断裂和抗噪问题,具有较好的边缘检测能力。
Clear and continuous edge feature is important to analyze and interpret SAR images. A new edge detection of SAR images is presented by analyzing regularization method. There are three steps. Firstly, using a modified regularization method reduce the speckle noise. Then, a statistical method is proposed to segment the target of interest. At last, edge detection is realized by a window method. Compared with traditional methods, experimental results with MSTAR dataset show that this method can maintain detail feature, resolve the broken edge and decrease noise efficiently. This algorithm has wonderful edge-detection performance.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2007年第10期864-867,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(60541001)
全国优秀博士论文作者专项基金资助项目(200443)
关键词
SAR图像
正则化
边缘检测
SAR images
regularization method
edge detection
