Fusion multi-channel satellite cloud images can provide a more comprehensive and reliable information for monitoring and forecasting weather conditions. A fusion method for satellite cloud images using Aliasing-suppression and Shift-invariance Contourlet Transform (AS&SICT) is presented. Firstly, in order to deal with the frequency aliasing and shift-variance problems of the original Contourlet transform, the aliasing-free filter bank is combined with non-subsampled directional filer banks (NDFB) to construct AS & SICT. Then, two channels of satellite images (infrared and visible) are decomposed into low-frequency and high-frequency directional sub-bands by AS&SICT. Next, low-frequency sub-band coefficients are fused by weighted regional energy rule while high-frequency sub-bands coefficients are fused by weighted regional variance rule. Finally, we get the fused cloud image by taking the inverse AS&SICT on the fusion coefficients. Experimental results show that the proposed fusion method can not only improve the resolution of infrared cloud image by joining the texture details of visible cloud image, but also keep the original brightness temperature information of infrared cloud image better.