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Low-rank and sparse representation for hyperspectral image processing: A review
Combining rich spectral and spatial information, a hyperspectral image (HSI) can provide a
more comprehensive characterization of the Earth's surface. To better exploit HSIs, a large …
more comprehensive characterization of the Earth's surface. To better exploit HSIs, a large …
Review of pixel-level remote sensing image fusion based on deep learning
The booming development of remote sensing images in many visual tasks has led to an
increasing demand for obtaining images with more precise details. However, it is impractical …
increasing demand for obtaining images with more precise details. However, it is impractical …
Multispectral and hyperspectral image fusion in remote sensing: A survey
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 …
spotlight. The combination of high spatial resolution MS images with HS data showing a …
Decoupled-and-coupled networks: Self-supervised hyperspectral image super-resolution with subpixel fusion
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 …
the aid of high spatial resolution multispectral (MS) images. Most prior works usually perform …
Zero-shot hyperspectral sharpening
Fusing hyperspectral images (HSIs) with multispectral images (MSIs) of higher spatial
resolution has become an effective way to sharpen HSIs. Recently, deep convolutional …
resolution has become an effective way to sharpen HSIs. Recently, deep convolutional …
Interpretable hyperspectral artificial intelligence: When nonconvex modeling meets hyperspectral remote sensing
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 …
geoscience and remote sensing (RS). In the past decade, enormous efforts have been made …
Edge-enhanced GAN for remote sensing image superresolution
The current superresolution (SR) methods based on deep learning have shown remarkable
comparative advantages but remain unsatisfactory in recovering the high-frequency edge …
comparative advantages but remain unsatisfactory in recovering the high-frequency edge …
Model-guided deep hyperspectral image super-resolution
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 …
hyperspectral images (HSI). Given the challenges of directly acquiring high-resolution …
Regularizing hyperspectral and multispectral image fusion by CNN denoiser
Hyperspectral image (HSI) and multispectral image (MSI) fusion, which fuses a low-spatial-
resolution HSI (LR-HSI) with a higher resolution multispectral image (MSI), has become a …
resolution HSI (LR-HSI) with a higher resolution multispectral image (MSI), has become a …
Fusing hyperspectral and multispectral images via coupled sparse tensor factorization
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 …
multispectral image (HR-MSI) to obtain a high spatial resolution hyperspectral image (HR …