Traditional image fusion method based Contourlet transform always ignores the relationship of the Contourlet coefficients.This paper proposes a novel ima ge fusion method based on Contourlet domain hidden Markov tree(HMT) model.The fusion method can strengthen the relationship among Contourlet coefficients and extract more detailed and exact information from the original images.Firstly,the original i mages are decomposed using Contourlet transform.Secondly,different frequenc y bands have different characteristics,so this paper designs the different fusion rules in different frequencies.The proposed method calculates likelihood function according to the parameters of Contourlet HMT.Finally the fused coefficients are reconstructed to obtain fusion results.Two sets of images are taken as experimen tal data,and subjective and objective standards are used to evaluate the results.Experimental results have verified the simplicity and effectiveness of the method.The results show t hat the proposed method can preserve much more information.The proposed fusion rule based on likelihood function can extract much more and exact characteristics for fused images.And it is an effec tive and feasible algorithm.