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The spatial and spectral resolution of remote sensing images are mutually restricted due to the limitation of sensor technology. Multispectral (MS) image has high spectral resolution, but low spatial resolution. While, panchromatic (PAN) image can provide high spatial resolution. Fusion of MS and PAN images is to get MS image with high resolution, which is a hot research in the field of remote sensing image processing. In this paper, a fusion algorithm of MS and PAN images is presented based on non-subsampled contourlet transform (NSCT) and Gram-Schmidt (GS) transform. Firstly, the low-resolution PAN image is synthesized by weighing each band of MS image whose weight coefficients are obtained by least squares estimation. MS image is decomposed by GS transform with the first GS component of the synthetic low-resolution PAN image. Secondly, one-level and three-level NSCT decomposition is performed on the synthetic low-resolution PAN image and PAN image, respectively. Low-frequency coefficients of low-resolution PAN image are as ones of the generated PAN image. High-frequency coefficients of first level decomposition of lowresolution PAN image and PAN image are fused according to region energy. The other level high-frequency coefficients of PAN image are as ones of the generated PAN image. Thirdly, the generated PAN image is reconstructed by the inverse NSCT with these coefficients. Lastly, inverse GS transform is performed to gain improved MS image by replacing the first GS component with the generated PAN image. The experiments conducted on Quickbird satellite images show that the proposed method is superior to the other typical methods, which improves the spatial resolution and has smaller spectral distortion.
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