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 …

Pan-sharpening involves integrating information from low-resolution multi-spectral and high-
resolution panchromatic images to generate high-resolution multi-spectral counterparts …

Global modeling-based image restoration frameworks have become popular. However, they
often require a high memory footprint and do not consider task-specific degradation. Our …

Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with
the aid of high spatial resolution multispectral (MS) images. Most prior works usually perform …

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 …

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 …

To solve object detection issues in infrared images, such as a low recognition rate and a
high false alarm rate caused by long distances, weak energy, and low resolution, we …

Pansharpening aims to fuse a registered high-resolution panchromatic image (PAN) with a
low-resolution hyperspectral image (LR-HSI) to generate an enhanced HSI with high …

Hyperspectral image super-resolution (HISR) is about fusing a low-resolution hyperspectral
image (LR-HSI) and a high-resolution multispectral image (HR-MSI) to generate a high …