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

Spectral unmixing aims at estimating the fractional abundances of pure spectral signatures
(also called endmembers) in each mixed pixel collected by a remote sensing hyperspectral …

Blind hyperspectral unmixing (HU), also known as unsupervised HU, is one of the most
prominent research topics in signal processing (SP) for hyperspectral remote sensing [1],[2] …

Hyperspectral unmixing is a crucial preprocessing step for material classification and
recognition. In the last decade, nonnegative matrix factorization (NMF) and its extensions …

Hyperspectral imaging is a promising tool for applications in geosensing, cultural heritage
and beyond. However, compared to current RGB cameras, existing hyperspectral cameras …

This paper presents a new method of minimum volume class for hyperspectral unmixing,
termed minimum volume simplex analysis (MVSA). The underlying mixing model is linear; …

Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers)
and their corresponding proportions (or abundances) from an observed hyperspectral …

This paper considers transmit optimization in multi-input multi-output (MIMO) wiretap
channels, wherein we aim at maximizing the secrecy capacity or rate of an MIMO channel …

In the late 1990s, Winter proposed an endmember extraction belief that has much impact on
endmember extraction techniques in hyperspectral remote sensing. The idea is to find a …

Live-cell fluorescence spectral imaging is an evolving modality of microscopy that uses
specific properties of fluorophores, such as excitation or emission spectra, to detect multiple …