Robust Blind Image Fusion for Misaligned Hyperspectral Imaging Data

The low spatial resolution of hyperspectral imaging can be significantly improved by fusing the hyperspectral image with a high resolution photograph. In most practical cases, however, the exact alignment between the fused images is not known a priori. In this work, we study how including a blind deconvolution approach in the mathematical model can help resolve translational misalignments. In particular, we investigate the influence of different initialization strategies. The efficiency of the proposed model is validated by numerical experiments using both simulated and real remote sensing data.