摘要: Aim at multiplicative speckle noise and little difference among targets in synthetic aperture radar (SAR) images, a target classification algorithm is proposed based on C-Means and support vector machines (SVMs). Its front part ad... 展开 Aim at multiplicative speckle noise and little difference among targets in synthetic aperture radar (SAR) images, a target classification algorithm is proposed based on C-Means and support vector machines (SVMs). Its front part adopts a C-Means clustering method to classify targets and suppress speckle noise in feature space, and its back part adopts an SVM classifier to improve classification accuracy in image space. Experimental results show that this algorithm can reduce the dimension of SVM and have a better classification performance using Ku-band SAR database. 收起