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 …

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 …

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 …

Hyperspectral image (HSI) denoising plays an important role in image quality improvement
and related applications. Convolutional neural network (CNN)-based image denoising …

Model-driven methods and data-driven methods have been widely developed for
hyperspectral image (HSI) denoising. However, there are pros and cons in both model …

Mixed noise (such as Gaussian, impulse, stripe, and deadline noises) contamination is a
common phenomenon in hyperspectral imagery (HSI), greatly degrading visual quality and …

Hyperspectral image (HSI) enjoys great advantages over more traditional image types for
various applications due to the extra knowledge available. For the nonideal optical and …

Hyperspectral image (HSI) mixed noise removal is a fundamental problem and an important
preprocessing step in remote sensing fields. The low-rank approximation-based methods …

With the maturation of satellite technology, Hyperspectral Remote Sensing (HRS) platforms
have developed from the initial ground-based and airborne platforms into spaceborne …

Hyperspectral image (HSI) qualities are limited by a mixture of Gaussian noise, impulse
noise, stripes, and deadlines during the sensor imaging process, resulting in weak …