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

Soil erosion is a direct product of the complex interactions between natural and
anthropogenic factors. Such factors vary over space and time, making the assessment of soil …

This work proposes a new shadow restoration method for hyperspectral images based on
nonlinear unmixing. A physical model is introduced to estimate the shadowed spectrum from …

Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …

Deep learning (DL) has aroused wide attention in hyperspectral unmixing (HU) owing to its
powerful feature representation ability. As a representative of unsupervised DL approaches …

In hyperspectral unmixing, the prevalent model used is the linear mixing model, and a large
variety of techniques based on this model has been proposed to obtain endmembers and …

Imaging spectrometers measure electromagnetic energy scattered in their instantaneous
field view in hundreds or thousands of spectral channels with higher spectral resolution than …

In order to achieve accurate hyperspectral image (HSI) classification, the convolutional
neural network (CNN) has been extensively utilized. However, most existing patch-based …

Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing
(RS) imaging has provided a significant amount of spatial and spectral information for the …

When considering the problem of unmixing hyperspectral images, most of the literature in
the geoscience and image processing areas relies on the widely used linear mixing model …