Aiming at the fusion problem of infrared and visible images with the same scene，a novel fusion algorithm based on neighbor statistic information is proposed.Firstly the source images are multi-scale decomposed，then many subband coefficients are obtained.Fusion methods of different fusion rules at high and low frequency are presented according to the physical characteristics of each subband coefficient.For the low frequency subband coefficients，the target and scene parameters based on neighbor statistic information are defined，and a weighted average fusion strategy with weighted coefficient adaptive variation is designed.For the high frequency subband coefficients，the neighborhood distribution characteristics parameter is defined，and a fusion strategy of coefficient comparison with neighbor statistic information modulation is designed.The experimental results show that the proposed algorithm can fuse infrared and visible images well.