For the fusion problem of infrared and visible light images with the same scene,an adaptive image fusion algorithm based on the second generation curvelet and wavelet transform is proposed.Firstly,source images are decomposed by the fast discrete curvelet transform,thus the coarse scale and fine scale coefficients are obtained at different scales and in various directions.Secondly,according to the different physical features of infrared and visible light images and human visual system features,the coarse scale and fine scale coefficients are fused using image fusion method based on discrete wavelet transform.In wavelet domain,for the low frequency coefficients,we present an adaptive fusion rule based on the physical features of infrared and visible light images;while for the high frequency coefficients,we present an adaptive fusion rule based on the neighborhood directional contrast combined with the local area matching.Fused curvelet coefficients are obtained through the inverse wavelet transform.Finally,the fusion image is obtained through the inverse fast discrete curvelet transform.The experimental results illustrate that the proposed algorithm is effective for extracting the characteristics of the original images.