Reconstructing a high-resolution hyperspectral image (HR-HSI) using a single low-
resolution hyperspectral image (LR-HSI) is a significant technique for increasing the spatial …

Unsupervised fusion-based hyperspectral imagery (HSI) super-resolution (SR) is an
essential task of HSI processing, which aims to reconstruct a high-resolution (HR) HSI using …

Hyperspectral images (HSIs) provide rich spectral information that has contributed to the
successful performance improvement of numerous computer vision and remote sensing …

Fusing a low spatial resolution (LR) hyperspectral image (HSI) with a high spatial resolution
(HR) multi-spectral image (MSI) is an effective way for HSI super-resolution. When the input …

Hyperspectral image (HSI) super-resolution (SR) is an important technique for improving the
spatial resolution of HSI. Recently, a method based on sparse representation improved the …

Benefiting from the high spectral resolution, hyperspectral image (HSI) owns the property of
discriminating material. However, the spatial resolution of HSIs is limited by the hardware …

Due to rich spectral information, hyperspectral images (HSIs) have been widely used in
various fields. However, limited by imaging systems, the low spatial resolution of HSIs has …

Hyperspectral images (HSIs) can describe the subtle differences in the spectral signatures of
materials. However, they have low spatial resolution due to various hardware limitations …

Hyperspectral imaging is unable to acquire images with high resolution in both spatial and
spectral dimensions yet, due to physical hardware limitations. It can only produce low spatial …

Hyperspectral image (HSI) super-resolution has gained great attention in remote sensing,
due to its effectiveness in enhancing the spatial information of the HSI while preserving the …