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The aim of image fusion is to integrate complementary information from several images to create a highly informative image which is more suitable for human visual perception or computer-processing tasks. Recent studies show that stationary wavelet transform (SWT) and nonsubsampled contourlet transform (NSCT) both turn out to be effective and efficient for image fusion. In order to take some complementary characteristics between the two multiresolution transformations simultaneously, we propose a hybrid multiresolution method by combining the SWT with the NSCT to perform image fusion. Two methods, serial NSCT aiding SWT (SNAS) and serial SWT aiding NSCT (SSAN), are studied and compared with some state-of-the-art methods. Experimental results demonstrate that the SSAN method performs better than SNAS and the individual multiresolution-based methods, such as NSCT, SWT, complex wavelet (CWT), curvelet (CVT) and wavelet-based contourlet (WBCT).