To overcome the shortcomings of the infrared and visible image fusion methods,combining with shift-invariance and higher directional sensitivity of fast finite shearlet transform(FFST),a novel adaptive multi-directional image fusion method based on FFST domain was proposed.Firstly,the FFST is used to decompose the strict registered images,and the low frequency sub-band coefficients and the high sub-band coefficients are obtained.Secondly,the fusion principle of low frequency sub-band coefficients is based on a constrained sparse algorithm for nonnegative matrix factorization,that is,a sparseness constraint is added to the original nonnegative matrix factorization algorithm,making the decomposition better,which can improve the definition of the image reconstruction.In order to obtain the detail information,a combined directional characteristics contrast is adopted to choose high frequency sub-band coefficients. Finally,the fused image is reconstructed by inverse FFST.The results show that the fused image reserves useful information of the source image and has clear overall outline.