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 …

Recent advances in airborne and spaceborne hyperspectral imaging technology have
provided end users with rich spectral, spatial, and temporal information. They have made a …

Non-local low-rank tensor approximation has been developed as a state-of-the-art method
for hyperspectral image (HSI) restoration, which includes the tasks of denoising …

Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the
performance of the subsequent HSI interpretation and applications. In this paper, a novel …

Hyperspectral image super-resolution by fusing high-resolution multispectral image (HR-
MSI) and low-resolution hyperspectral image (LR-HSI) aims at reconstructing high resolution …

In this paper, we propose a spectral–spatial unified network (SSUN) with an end-to-end
architecture for the hyperspectral image (HSI) classification. Different from traditional …

The spectral and the spatial information in hyperspectral images (HSIs) are the two sides of
the same coin. How to jointly model them is the key issue for HSIs' noise removal, including …

Hyperspectral anomaly detection (HAD) is an important hyperspectral image application.
HAD can find pixels with anomalous spectral signatures compared with their neighbor …

Deep networks have achieved excellent performance in learning representation from visual
data. However, the supervised deep models like convolutional neural network require large …

Mixed noise pollution in HSI severely disturbs subsequent interpretations and applications.
In this technical review, we first give the noise analysis in different noisy HSIs and conclude …