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 …

Machine learning, particularly deep learning (DL), has become a central and state-of-the-art
method for several computer vision applications and remote sensing (RS) image …

Multispectral image (MSI) and hyperspectral image (HSI) fusion can combine the best of
both worlds to produce images with both high spatial and spectral resolutions. In this article …

Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to
understand the current ecological status of the Ferghana Basin and to analyze the …

Pansharpening aims to fuse low-resolution multi-spectral image and high-resolution
panchromatic (PAN) image to produce a high-resolution multi-spectral (HRMS) image. In …

Probing the long-term spatiotemporal patterns of wetland vegetation changes and their
response to climate change and human activities is critical to make informed decisions …

Realistic hyperspectral image (HSI) super-resolution (SR) techniques aim to generate a high-
resolution (HR) HSI with higher spectral and spatial fidelity from its low-resolution (LR) …

INTRODUCTION Individuals living in rural communities are at heightened risk for
Alzheimer's disease and related dementias (ADRD), which parallels other persistent place …

Fine spatial resolution remote sensing images are crucial sources of data for monitoring the
Earth's surface. Due to defects in sensors and the complicated imaging environment …

Traditional approaches mainly fuse a hyperspectral image (HSI) with a high-resolution
multispectral image (MSI) to improve the spatial resolution of the HSI. However, such …