Hyperspectral unmixing has been an important technique that estimates a set of
endmembers and their corresponding abundances from a hyperspectral image (HSI) …

In remote sensing, hyperspectral unmixing is very challenging inverse ill-posed problem
which does not have closed-form solution. Since more than three decades, several …

In this paper, we propose a novel approach for spectral unmixing based on unsupervised
learning using autoencoder with Inhomogeneous Gaussian Markov random field (IGMRF) …

At present, an emerging technique called the algorithm unrolling approach has attracted
wide attention, because it is capable of developing efficient and interpretable layers to …

This letter proposes a simple, fast, yet efficient sparse hyperspectral unmixing algorithm. The
proposed method consists of three main steps. First, a coarse approximation of the …

Multispectral unmixing (MU) is critical due to the inevitable mixed pixel phenomenon caused
by the limited spatial resolution of typical multispectral images in remote sensing. However …

Spectral unmixing (SU) aims at decomposing the mixed pixel into basic components, called
endmembers with corresponding abundance fractions. Linear mixing model (LMM) and …

Hyperspectral image (HSI) Super-resolution (SR) methods enhance the spatial resolution. In
this paper, we propose a novel SR approach for HSIs by making use of spectral unmixing …