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 …
Recent advances and new guidelines on hyperspectral and multispectral image fusion
Hyperspectral image (HSI) with high spectral resolution often suffers from low spatial
resolution owing to the limitations of imaging sensors. Image fusion is an effective and …
resolution owing to the limitations of imaging sensors. Image fusion is an effective and …
Multispectral and hyperspectral image fusion in remote sensing: A survey
G Vivone - Information Fusion, 2023 - Elsevier
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 …
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 …
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 …
Learning a low tensor-train rank representation for hyperspectral image super-resolution
Hyperspectral images (HSIs) with high spectral resolution only have the low spatial
resolution. On the contrary, multispectral images (MSIs) with much lower spectral resolution …
resolution. On the contrary, multispectral images (MSIs) with much lower spectral resolution …
Spatial-spectral structured sparse low-rank representation for hyperspectral image super-resolution
Hyperspectral image super-resolution by fusing high-resolution multispectral image (HR-
MSI) and low-resolution hyperspectral image (LR-HSI) aims at reconstructing high resolution …
MSI) and low-resolution hyperspectral image (LR-HSI) aims at reconstructing high resolution …
Deep hyperspectral image sharpening
Hyperspectral image (HSI) sharpening, which aims at fusing an observable low spatial
resolution (LR) HSI (LR-HSI) with a high spatial resolution (HR) multispectral image (HR …
resolution (LR) HSI (LR-HSI) with a high spatial resolution (HR) multispectral image (HR …
Hyperspectral image super-resolution via subspace-based low tensor multi-rank regularization
Recently, combining a low spatial resolution hyperspectral image (LR-HSI) with a high
spatial resolution multispectral image (HR-MSI) into an HR-HSI has become a popular …
spatial resolution multispectral image (HR-MSI) into an HR-HSI has become a popular …
Hyperspectral super-resolution: A coupled tensor factorization approach
Hyperspectral super-resolution refers to the problem of fusing a hyperspectral image (HSI)
and a multispectral image (MSI) to produce a super-resolution image (SRI) that admits fine …
and a multispectral image (MSI) to produce a super-resolution image (SRI) that admits fine …