%0 Journal Article
%T SAR target recognition using PCA, ICA andGabor wavelet decision fusion<br>PCA、ICA和Gabor小波决策融合的SAR目标识别
%A HUAN Ruohong
%A ZHANG Ping
%A PAN Yun
%A <br>宦若虹
%A 张平
%A 潘赟
%J 遥感学报
%D 2012
%I 
%X A method for Synthetic Aperture Radar (SAR) image target recognition based on Principal Component Analysis (PCA),Independent Component Analysis (ICA) and Gabor wavelet decision fusion is presented in this paper. PCA, ICA and Gaborwavelet transformation were used to extract feature vectors from SAR target images, respectively. Three Support Vector Machine(SVM) classifiers were applied to classify the feature vectors extracted via three algorithms, respectively. Ranking based decisionfusion algorithm was then used to fuse the outputs of three classifiers. The final classification decision result was obtained fromthe output of the fuser. Experiments were implemented with three military targets in MSTAR database. The experimental resultsshow that the probability of correct classification obtained by PCA, ICA and Gabor wavelet decision fusion is better than that attainedby any of the individual feature. Therefore, it is concluded that the method proposed in this paper advances the probabilityof correct classification and can be an effective approach for SAR image target recognition.
%K SAR
%K target recognition
%K decision fusion
%K PCA
%K ICA
%K Gabor wavelet<br>合成孔径雷达
%K 目标识别
%K 决策融合
%K 主成分分析
%K 独立分量分析
%K Gabor小波
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=2C2DE33E892A88200E59BF7C69E6F445&yid=99E9153A83D4CB11&vid=7801E6FC5AE9020C&iid=0B39A22176CE99FB&sid=30897FA31CA3354D&eid=6826CBE9C80ACB20&journal_id=1007-4619&journal_name=遥感学报&referenced_num=0&reference_num=19