Multi-Image Fusion for Super-Resolving Individual Sentinel-2 Images

Insufficient spatial resolution remains a serious obstacle for many potential applications of Sentinel-2 images. Therefore, a number of super-resolution techniques have been proposed, including single-image and multi-image approaches. While the former may hallucinate (rather than reconstruct) the image details, the latter are underpinned with information fusion that helps address these issues. However, given the five-days-long revisit time, a multi-temporal series of Sentinel-2 images contains temporal changes that affect the performance of multi-image super-resolution. In this paper, we propose a solution that allows for selecting a single image in the series to specify the point in time, at which the scene should be reconstructed. We report the results of our extensive experiments which confirm that our approach leads to improving the reconstruction quality, while preserving the temporal consistency. Importantly, the proposed solutions are potentially applicable to a variety of existing super-resolution techniques and they are not limited to Sentinel-2 images.