Many satellites, including the recently launched Pléiades, decouple the
acquisition of a panchromatic image at high spatial resolution
from the acquisition of a multispectral image at lower spatial resolution.
The pansharpening problem refers to the fusion process of inferring a
high-resolution multispectral image
from a high-resolution panchromatic image and a low-resolution
To solve this problem, we present a functional that incorporates a nonlocal regularization term and two fidelity terms. The first one imposes the spatial correlation between the high-resolution panchromatic data and the same band from the pansharpened image based on the information from the low-resolution multispectral image while the second one preserves the colors from the low-resolution channels.
This model is applied on real images from the satellite Pléiades thanks to a joint project with CNES, the french spatial agency.