关键词: 遥感图像融合,Contourlet变换,粒子群优化,结构相似度

Abstract: In order to effectively optimize the retention of multi-spectral characteristic and the reservation of spatial information in the fusion image,we presented a remote sensing image fusion method by coupling contourlet transform and particle swarm optimization (PSO).The optimized fusion image is achieved by setting the PSO fitness functions which depend on the objective evaluation indexes of fusion image.The optimal weighting coefficient of lowpass sub-band and the best threshold for the regional structure similarity of highpass sub-band are adaptively obtained by PSO.Firstly,the panchromatic image and I component of multispectral image are decomposed respectively by using the contourlet transform.According to the different feature information,the difference between entropy and relative deviation is regarded as PSO fitness function to adaptively find the best weighting coefficient by the optimized algorithm in the lowpass sub-band.Meanwhile,the structure similarity is considered as PSO fitness function to search the best threshold p and the fusion rules of regional structure similarity is used to fuse image in the highpass sub-band.Finally,the fused image is reconstructed by inverse transform of contourlet and IHS.The simulation experiment results show that the proposed algorithm can effectively preserve the spectral information and spatial information of the original images.

Key words: Remote sensing image fusion,Contourlet transform,Particle swarm optimization,Structural similarity