Spectral Diversity Enhancement for Pansharpening

Pansharpening is to generate a synthetic image with high spatial resolution and high spectral resolution via fusing panchromatic (PAN) and multispectral (MS) images. In most traditional pansharpening methods, the original MS image is firstly interpolated to the same size of PAN image by analytical interpolations. However, these interpolated methods could cause false spectral information due to ignoring mixed spectral characteristics in the MS image. To enhance the spectral diversity of upsampled MS image, we use the spatial structure information in PAN image to support the pansharpening in this paper. By introducing the superpixel structure for PAN image, the processible mixed pixels can be screened out in corresponding MS locations, and the other MS locations are considered to be occupied by pure pixels. For the pure and mixed pixels, their upsampling MS results can be obtained via a directly expending manner and a sparse representation manner respectively. Two different detail injection strategies are used for assessing the performance of analytical interpolations and our approach for pansharpening. Experimental results demonstrate that our method achieves the appreciable improvements with respect to analytical interpolations.