关键词: 遥感图像分类, 图像融合, 非下采样Contourlet, 最小二乘支持向量机

Abstract: A new method of remote sensing image land cover classification based on NonSubsampled Contourlet Transform（NSCT） and Least Squares Support Vector Machines（LSSVM） is proposed.This method selects best band features dynamically to composite a multispectral image，and then fuses it with panchromatic image based on NSCT and stationary wavelet transform for better spatial resolution of multispectral image，performs land cover classification on the fused image based on LSSVM.The experimental results show that the proposed method can effectively preserve spectral information and improve spatial information of the remote sensing image，provide more reliable classification features of ground objects，improve classification precision，and outperform the traditional classifier based on minimum distance，maximum likelihood，Bayesian，back propagation neural network.

Key words: remote sensing image classification, image fusion, NonSubsampled Contourlet Transform（NSCT）, Least Squares Support Vector Machines（LSSVM）