With the extremely rapid advances in remote sensing (RS) technology, a great quantity of
Earth observation (EO) data featuring considerable and complicated heterogeneity are …

Image fusion, which refers to extracting and then combining the most meaningful information
from different source images, aims to generate a single image that is more informative and …

Owing to the limitations of imaging sensors, it is challenging to obtain a medical image that
simultaneously contains functional metabolic information and structural tissue details …

Infrared and visible image fusion is aims to generate a composite image that can
simultaneously describe the salient target in the infrared image and texture details in the …

Recently, unmixing-based networks have shown significant potential in unsupervised
multispectral-aided hyperspectral image super-resolution (MS-aided HS-SR) task …

The fusion of multispectral (MS) and hyperspectral (HS) images has recently been put in the
spotlight. The combination of high spatial resolution MS images with HS data showing a …

Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

Machine learning (ML) is influencing the literature in several research fields, often through
state-of-the-art approaches. In the past several years, ML has been explored for …

Fusing hyperspectral images (HSIs) with multispectral images (MSIs) of higher spatial
resolution has become an effective way to sharpen HSIs. Recently, deep convolutional …

A Transformer has received a lot of attention in computer vision. Because of global self-
attention, the computational complexity of Transformer is quadratic with the number of …