This article brings together the advances of multisource and multitemporal data fusion
approaches with respect to the various research communities and provides a thorough and …

By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …

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

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 (HS) imaging, also known as image spectrometry, is a landmark technique in
geoscience and remote sensing (RS). In the past decade, enormous efforts have been made …

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

The trade-off between spatial and spectral resolution is one of the fundamental issues in
hyperspectral images (HSI). Given the challenges of directly acquiring high-resolution …

Fusing a low spatial resolution hyperspectral image (LR-HSI) with a high spatial resolution
multispectral image (HR-MSI) to obtain a high spatial resolution hyperspectral image (HR …

Hyperspectral images (HSIs) with high spectral resolution only have the low spatial
resolution. On the contrary, multispectral images (MSIs) with much lower spectral resolution …

In recent years, enormous efforts have been made to design image-processing algorithms to
enhance the spatial resolution of hyperspectral (HS) imagery. One of the most commonly …