A remote sensing image fusion method is proposed to enhance fusion image quality and fusion efficiency. This method is based on the combination of discrete wavelet and multiscale morphological transform in the IHS color space. First, the three-band multispectral image is converted into the IHS color space to obtain the intensity (I), hue (H), and saturation (S) components. Second, the discrete wavelet transform is used to decompose the I component and PAN images, each of which is decomposed into a set of high-frequency detail images at different scales and one low-frequency approximation image. Then, the dual-channel multiscale morphological transform is constructed based on the idea of à trous algorithm. Upon this, the high-frequency detail images are further decomposed by multiscale morphological gradient transform to extract the edge details information. Two low-frequency approximate images are decomposed by multiscale morphological top-hat and bottom-hat transform to extract the light and dark details information. The decomposition coefficients are fused by designed fusion rules. Finally, the corresponding inverse transform is conducted to reconstruct the fused image. The experimental results have shown that the proposed method performs well, in both subjective and objective evaluations. Compared with other seven hybrid methods popularly applied in image fusion, the proposed method is superior in the 12 indicators. In addition, it has significantly reduced the computational cost in the fusion process. The results have proved that the proposed method not only fully preserves the spectral information of the source MS image but also inherits the rich spatial details of the source PAN image while, achieves high efficiency in image fusion.