Data fusion of satellite imagery for generation of daily cloud free images at high resolution level
This work addresses the challenge of obtaining reliable daily high-resolution satellite imagery for applications like environmental monitoring, though it appears incremental as it builds on existing data fusion methods.
The paper tackles the problem of generating daily cloud-free satellite images at high resolution by fusing Sentinel-2 and MODIS data, using a variational approach to address cloud corruption and noise in Sentinel-2 images.
In this paper we discuss a new variational approach to the Date Fusion problem of multi-spectral satellite images from Sentinel-2 and MODIS that have been captured at different resolution level and, arguably, on different days. The crucial point of our approach that the MODIS image is cloud-free whereas the images from Sentinel-2 can be corrupted by clouds or noise.