Hyperspectral Pansharpening: Review and Future Perspectives

In this paper, a representative set of state-of-the-art methods for hyperspectral pansharpening, comprising both model- and deep learning-based ones, are reviewed and compared on four datasets from the PRISMA mission. The experimental analysis has been carried out using the most credited pansharpening quality indexes, complemented by a subjective visual inspection of sample results. The obtained outcomes have provided us a preview of the strengths and weaknesses of the latest solutions to the problem at hand, paving the way for future research lines from both the methodological and quality assessment perspectives.