The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

A hyperspectral image (HSI) is a collection of several narrow-band images that span a wide
spectral range. Each band reflects the same scene, composed of various objects imaged at …

Mixed pixels exist widely in remotely sensed images. To obtain more reliable land cover
information than traditional hard classification, spectral unmixing methods have been …

Band selection (BS), which can reduce the spectral dimensionality effectively, has become
one of the most popular topics in hyperspectral image (HSI) analysis. Recently, sparse …

The fusion of hyperspectral (HS) and multispectral (MS) images with complementary high
spectral and high spatial resolution information has been successfully applied to improve …

Unsupervised band selection identifies informative bands in hyperspectral images (HSIs)
without prior labeling, reducing spectral redundancy. Besides spectral information, the …

Limited to the low spatial resolution of the hyperspectral imaging sensor, mixed pixels are
inevitable in hyperspectral images. Therefore, to obtain the endmembers and corresponding …

With a low spectral resolution hyperspectral sensor, the signal recorded from a given pixel
against the complex background is a mixture of spectral contents. To improve the accuracy …

Hyperspectral images have acquired an increasing interest in the scientific and civil
community to detect or classify materials by their spectral signature in remote sensing …

Sugar beet varieties were classified based on hyperspectral technology and the Extreme
Learning Machine (ELM) algorithm. The influences of seven pretreatment methods, namely …