极化SAR图像中的弱小舰船目标检测

结合最新的子空间数据分析方法--非负矩阵分解(nonnegative matrix factorization, NMF),对极化合成孔径雷达(synthetic aperture radar, SAR)图像中的弱小舰船目标提出一种全新的有效检测方法。该方法利用极化协方差矩阵分解,得到包含极化图像能量的特征值组,组成满足NMF要求的非负矩阵;然后采用稀疏限制的NMF来提取其中的主要特征,以此将舰船目标检测出来。采用国内全极化和双极化实测海洋数据进行实验,验证了本文方法的有效性。

Weak ship detection in polarimetric SAR image

Combining with nonnegative matrix factorization (NMF)-a new subspace data analysis method, a novel method for weak ship targets detection is proposed for polarimetric synthetic aperture radar (SAR) image detection. By eigendecomposition of the polarimetric covariance matrix, the eigenvalue sets containing the energy of the polarimetric SAR image can be achieved. Using these eigenvalue sets, the non-negative matrix can be composed. Then the dominating feature of the polarimetric SAR image is extracted using NMF with sparseness constraints, hence, the weak ship targets can be detected. The ocean measured data of both the fully and dual polarimetric SAR have been utilized to validate the effectiveness of the proposed method.