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An improved non-subsampled contourlet transform-based hybrid pan-sharpening algorithm

Multi-resolution analysis (MRA) is a useful technique for multispectral (MS) image pan-sharpening. To overcome the limitation of the conventional wavelet-based method, multi-directional MRA approaches have been proposed to provide an efficient directional information representation. In this paper, we present a new hybrid method for MS image pan-sharpening that uses non-subsampled contourlet transform (NSCT) as the MRA tool, and followed by a high-pass detail-injection model. Particularly, to further enhance the spatial resolution of the MS image, and in the meantime, produce a high spectral quality, we take account of the dissimilarity between the spatial details of MS image and decomposed panchromatic image of NSCT, and introduce a fast and effective means to deal with the problem. Experiments on four remote sensing data sets show the superiority of the presented approach over other typical pan-sharpening methods.