Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research
field and is considered a non-invasive tool for tissue diagnosis. This review article gives a …

In this work, many of the fundamental and advanced spectral processing methods available
to geologic remote sensing are reviewed. A novel categorization scheme is proposed that …

Sparse unmixing has been recently introduced in hyperspectral imaging as a framework to
characterize mixed pixels. It assumes that the observed image signatures can be expressed …

In many computer vision applications, obtaining images of high resolution in both the spatial
and spectral domains are equally important. However, due to hardware limitations, one can …

Linear spectral unmixing is the practice of decomposing the mixed pixel into a linear
combination of the constituent endmembers and the estimated abundances. This paper …

Hyperspectral sensors record the reflectance from the Earth's surface over the full range of
solar wavelengths with high spectral resolution. The resulting high-dimensional data contain …

Hyperspectral unmixing is one of the most important techniques in analyzing hyperspectral
images, which decomposes a mixed pixel into a collection of constituent materials weighted …

Spectral unmixing aims at estimating the fractional abundances of a set of pure spectral
materials (endmembers) in each pixel of a hyperspectral image. The wide availability of …

Spectral unmixing is an important technique for remotely sensed hyperspectral data
exploitation. It amounts to identifying a set of pure spectral signatures, which are called …

Sparse unmixing, as a semisupervised unmixing method, has attracted extensive attention.
The process of sparse unmixing involves treating the mixed pixels of hyperspectral imagery …