The traditional image fusion methods based on multi-scale transform can easily loss the details of visible image,weaken the infrared target information and reduce the image contrast.To solve the problem,a fusion method of infrared and visible images is proposed based on bidimensional empiric al mode decomposition(BEMD)and Gaussian fuzzy logic (GFL).Firstly,the source images are decompose d to obtain intrinsic modes(high-frequency component) and trend terms(low-frequency component)by BEM D.Secondly,trend terms are combined properly by using the GFL based fusion rule,and intrinsic modes are me rged by using regional contrast method based on neighborhood characteristics.Finally,the fusion image is obtai ned by performing the inverse BEMD transform on the combined coefficients.The experimental results prove t hat the proposed method outperforms the traditional multi-scale methods for infrared-visible images fu sion.Subjectively,the proposed fusion method can improve the quality of fusion image by preserving the details of source visible image and highlighting the targets of source infrared image.Objectively,the results of t he proposed fusion method are obviously better than those of the traditional multi-scale methods in the objec tive evaluation values,such as information entropy (IE),standard deviation (SD),average gradient (AG),mutual information (MI) and spatial frequency (SF).