Recent advances in airborne and spaceborne hyperspectral imaging technology have
provided end users with rich spectral, spatial, and temporal information. They have made a …

This article gives a survey of state-of-the-art methods for processing remotely sensed big
data and thoroughly investigates existing parallel implementations on diverse popular high …

Hyperspectral imaging (HSI) is a competitive remote sensing technique in several fields,
from Earth observation to health, robotic vision, and quality control. Each HSI scene contains …

Most existing endmember extraction techniques require prior knowledge about the number
of endmembers in a hyperspectral image. The number of endmembers is normally estimated …

Endmember estimation plays a key role in hyperspectral image unmixing, often requiring an
estimation of the number of endmembers and extracting endmembers. However, most of the …

Unmixing is an important issue of hyperspectral images. Most unmixing methods adopt
linear mixing models for simplicity. However, multiple scattering usually occurs between …

Endmember extraction algorithms (EEAs) play a crucial role in hyperspectral image (HSI)
perception, and yet they normally suffer from three flaws: 1) High computational burden, 2) …

In recent years, the data generation rate of high-resolution optical satellites is increasing
rapidly, and this situation brings massive stress to the data downloading link and data …

Hyperspectral imaging systems are a powerful tool for obtaining surface information in many
different spectral channels that can be used in many different applications. Nevertheless, the …

The identification of pure spectral signatures (endmembers) in remotely sensed
hyperspectral images has traditionally focused on the spectral information alone. Recently …