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

Considering the labeled samples may be difficult to obtain because they require human
annotators, special devices, or expensive and slow experiments. Semi-supervised learning …

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 …

Transformers have intrigued the vision research community with their state-of-the-art
performance in natural language processing. With their superior performance, transformers …

In this paper, we present a spatial spectral hyperspectral image (HSI) mixed-noise removal
method named total variation (TV)-regularized low-rank matrix factorization (LRTV). In …

Blind hyperspectral unmixing is the process of expressing the measured spectrum of a pixel
as a combination of a set of spectral signatures called endmembers and simultaneously …

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

The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

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 …