Hyperspectral sensors enable the study of the chemical properties of scene materials
remotely for the purpose of identification, detection, and chemical composition analysis of …

Data acquired from multichannel sensors are a highly valuable asset to interpret the
environment for a variety of remote sensing applications. However, low spatial resolution is …

Optical analysis techniques are used recently to detect and identify the objects from a large
scale of images. Hyperspectral imaging technique is also one of them. Vision of human eye …

The presence of shadows has always been a troublesome problem in image processing
and can also affect spectral unmixing with hyperspectral remote sensing images. Traditional …

Hyperspectral unmixing has received increasing attention as a technique for estimating
endmember spectra and fractional abundances of land covers. Encoding high-dimensional …

Background Cannabis possesses a rich spectrum of phytochemicals ie cannabinoids,
terpenes and phenolic compounds of industrial and medicinal interests. Most of these high …

Hyperspectral unmixing, which estimates end-members and their corresponding abundance
fractions simultaneously, is an important task for hyperspectral applications. In this article …

Boundary pixels of rivers are subject to a spectral mixture that limits the accuracy of river
areas extraction using conventional hard classifiers. To address this problem, unmixing and …

Most nonlinear mixture models and unmixing methods in the literature assume implicitly that
the degrees of multiple scatterings at each band are the same. However, it is commonly …

Efficient compression is pertinent for the convenient storage, transmission, and processing
of modern high-resolution hyperspectral images (HSI). We propose a high-performance HSI …