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 …

Terrestrial water, an important indicator of inland hydrological status, is sensitive to land use
cover change, natural disaster and climate change. An accurate and robust water extraction …

Although considerable effort has been dedicated to improving the solution to the
hyperspectral unmixing problem, non-idealities such as complex radiation scattering and …

Regularization is effective in mitigating the ill-condition existing in inverse problems. With
respect to the ill-conditioned prestack seismic inversion, regularization aims to stabilize the …

As a widely concerned research topic, many advanced algorithms have been proposed for
hyperspectral unmixing. However, they may fail to accurately identify endmember signatures …

Prestack seismic inversion is an ill-posed problem and must be regularized to stabilize the
inverted results. In particular, edge-preserving regularization with prior constraints based on …

In this article, a wavelet-based energy minimization framework is developed for joint
estimation of endmembers and abundances without assuming pure pixels while considering …

The prestack seismic inversion effectively transforms reflection data into elastic parameters
attributed to rock properties, which has enabled us to explore subsurface in detail. Because …

Accurate retrieval of canopy nutrient content has been made possible using visible-to-
shortwave infrared (VSWIR) imaging spectroscopy. While this strategy has often been tested …