A remote sensing image fusion algorithm is presented based on wavelet transform and sparse representation for the fusion of multi-spectral image and panchromatic image. The algorithm makes full use of the wavelet transform which has the advantage of maintaining spectral information. First

the intensity-hue-saturation (IHS) transform is applied to the multi-spectral image. Then

the obtained corresponding high-and low-frequency coefficients are transformed by the monolayer wavelet transform on the intensity component and the panchromatic image. According to the different characteristics of the low and high frequency coefficients

the low-frequency coefficients cannot be considered to be "sparse". The low-frequency images are obtained their sparse coefficients through sparse representation. The high-frequency coefficients can be considered to be "sparse". A fusion rule

which uses the image information

was taken to compute the high fusion coefficients. Finally

the fused results are obtained through wavelet inverse transform and IHS inverse transform. The experimental results prove that the proposed method improve the spatial resolution and better maintain the spectral characteristics.