Image classification algorithm based on the RBF neural network and K-means

被引:55
作者
Rollet, R [1 ]
Benie, GB
Li, W
Wang, S
Boucher, JM
机构
[1] Univ Sherbrooke, Ctr Applicat & Rech Teledetect, CARTEL, Sherbrooke, PQ J1K 2R1, Canada
[2] Ecole Natl Super Telecommun Bretagne, Brest, BELARUS
关键词
D O I
10.1080/014311698214398
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
This Letter presents the implementation of an algorithm using the radial basis function (RBF) neural networks combined with the technique of K-means for the classification of optical and radar remote sensing images. During the convergence of RBF networks, K-means serves for the initialization of class centres. An automatic self-organizing classification algorithm is constructed based on the RBF networks and split and merge technique. Experimental results show that this algorithm is an effective classifier compared to some conventional methods.
引用
收藏
页码:3003 / 3009
页数:7
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