中文摘要：

为了使融合图像在显著提高空间分辨率的同时，最大限度地融入多光谱图像的光谱信息，提出了一种结合Canny算子与非下采样Contourlet变换的粒子群优化的遥感图像融合方法。首先在IHS变换的基础上，利用Canny算子对全色图像进行边缘提取，根据边缘分布特征对全色图像和多光谱图像I分量进行边缘特征融合得到边缘加强的全色图像，然后对新的全色图像和多光谱图像I分量分别进行非下采样Contourlet变换，并在低频子带采用有选择性的加权求和融合规则，对于高频方向子带先利用粒子群优化算法寻找结构相似度的最优阈值p，再采用基于区域结构相似度的融合规则，最后经NSCT和IHS逆变换获得融合图像。仿真实验结果表明：提出的算法能很好地兼顾全色图像细节信息的保留和多光谱图像光谱信息的保持。

英文摘要：

In order to significantly improve the spatial resolution of the fused image and maximally fuse the spectral information of multi-spectral images,it presents a Particle Swarm Optimized(PSO)remote sensing image fusion method by combining Canny operator with Nonsubsampled Contourlet Transform(NSCT)in this paper.Firstly,the edge information of the panchromatic image is distinguished to the non-edge by Canny operator on the basis of IHS transform,and the edge of the panchromatic image is enhanced by fusing the panchromatic image and I component of multi-spectral image according to the characteristics of edge distribution.Then,the enhanced panchromatic image and I component of multispectral image are respectively decomposed by NSCT,the method of selective weighted summation is used in the lowpass sub-band,the PSO is performed to search the best threshold p and the fusion rules of regional structure similarity areused in the highpass sub-band.Finally,the fused image is reconstructed by inverse transform of NSCT and IHS.The simulation experiment results show that the algorithm can maintain a good balance between the detail information and spectral information of the original images.