Pan-sharpening using 2D CCA

Pan-sharpening is a multisource fusion process which combines a low-resolution multispectral (LRM) image with a high-resolution panchromatic (HRP) image to fuse a high-resolution multispectral (HRM) image. However, the previous methods only focused on the original spatial space or simple feature space without considering the strong correlations between HRM and HRP images. In this paper, a novel pan-sharpening method on a common feature space is proposed based on two-dimensional canonical correlation analysis (2D CCA). 2D CCA is first used to train four projection matrices from the HRM training images, the HRP training images and their degraded ones. A common feature space is then established by maximizing the statistical correlations between intrinsic structures of low- and high-resolution images. Then the k-nearest neighbour selection of the input LRM image patches is conducted in the derived feature space to estimate the reconstruction weights. Finally, the pan-sharpened HRM is reconstructed by neighbou...