A simple nonlocal back-projection unfolded network for pansharpening

Pansharpening is the fusion process that combines the geometry of a high-resolution panchromatic image with the spectral information encoded in a low-resolution multispectral image. We introduce a back-projection method to minimize the reconstruction error between the target image and the output produced by the Brovey pansharpening model. We replace the back-projection kernel with a residual network that incorporates a nonlocal module, exploiting self-similarity and built upon the multi-head attention mechanism. Experimental validation showcases that our method achieves state-of-the-art results.