The definition of image fusion is described by a figure. The evolution of image fusion technique is reviewed and the adventage and shortcoming of those image fusion methods are briefly explained as well. By analyzing formulation theory of remote sensing satellite image in frequency domain, it is concluded that high-resolution image covers more wide frequency domain and low-resolution multi-spectral image covers relatively smaller frequency domain. The requirement for combining the high frequency part of high resolution image with the low frequency part of the low resolution multi-spectral image is arisen from several user groups. Some possibilities to combine the high frequency part of the high resolution images with the low resolution images which are called image fusion methods are proposed by different application purposes. The theoretical basis of image fusion is then given. The basic theory and advantage of wavelets, Mallat algorithm and Wallis transformation are introduced. Wavelets analysis can be used to decompose the image orthogonal while keeping the information of the original image and Wallis transformation can be used to enhance the contrast of weak contrast area and remove the noise. It is found that those benefits of wavelet analysis, Wallis transformation can be used for image fusion. IHS transformation is a common image fusion technique. It can be used to transfer RGB image channels from RGB space to IHS channels of IHS space, the intensity of the image is separated from hue and saturation channels. It provides the possibility to keep the colorful characteristics of the original color composite while modulating the intensity channel. An image fusion method which integrates the advantages of Wallis transformation,wavelets analysis and IHS transformation is proposed. Median filter is also used to remove the noise of the hue and saturation channel. A test area of the suburban area of western Beijing city is chosen to check the proposed image fusion process. The test site includes different topographic geomorphies such as mountain area,rural area, lakes and urban area. It is useful to check the proposed image fusion method whether it can enhance the resolution by checking the details of the mountain area and the roads of urban area and keep the original color composite by checking whether the color of lake surface and the land cover is changed or not. Some quantitative and qualitative evaluation methods are introduced and the results show that details of high resolution image are added to the low resolution multi-spectral images while keeping the spectral characteristics of the original image.