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 …

This study proposes a novel general image fusion framework based on cross-domain long-
range learning and Swin Transformer, termed as SwinFusion. On the one hand, an attention …

In this paper, a squeeze-and-decomposition network (SDNet) is proposed to realize multi-
modal and digital photography image fusion in real time. Firstly, we generally transform …

Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

Visible images contain rich texture information, whereas infrared images have significant
contrast. It is advantageous to combine these two kinds of information into a single image so …

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 …

Pan-sharpening aims to generate high-resolution multi-spectral (MS) images by fusing PAN
images and low-resolution MS images. Despite its great advances, most existing pan …

The fusion of multisource remote sensing (RS) data has demonstrated significant potential in
target recognition and classification tasks. However, there is limited emphasis on capturing …