Most of the commonly used image fusion methods have the same limitation, only one fused result is possible by using each of the method, the users have no control over how much spatial detail or spectral information should be retained. A wavelet-based adjustable image fusion method is presented. The two images are decomposed into sub-images with wavelet transform, respectively. By introducing two parameters that can adjust the fused image, these sub-images are fused in wavelet space. A fused image is achieved by inverse wavelet transform. To compare the performances of the proposed method with those of the commonly used image fusion methods, such as the usual wavelet fuser, the intensity-hue-saturation (IHS) fuser, and the principal component analysis (PCA) fuser, the SPOT and the landsat thematic mapper (TM) images are used to perform the experiment. The results show that the balance between spectral characteristics preservation and high spatial resolution retention can be achieved at different levels in image fusion. With some combination of the parameters, the visual effects and the statistical parameters indicate that the fused results are slightly better than those of the commonly used image fusion methods.