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

Spectral unmixing is the process of decomposing the spectral signature of a mixed pixel into
a set of endmembers and their corresponding abundances. Endmembers are spectra of the …

高光谱成像技术具有光谱分辨率高, 图谱合一的独特优势, 是遥感技术发展以来最重大的科技
突破之一. 中国的高光谱遥感发展与国际基本同步, 在国家和省部级科研项目的支持下 …

Imaging spectrometers measure electromagnetic energy scattered in their instantaneous
field view in hundreds or thousands of spectral channels with higher spectral resolution than …

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of
the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded …

Given only the collected hyperspectral data, unmixing aims at obtaining the latent
constituent materials and their corresponding fractional abundances. Recently, many …

Over the past decade, the incorporation of spatial information has drawn increasing attention
in multispectral and hyperspectral data analysis. In particular, the property of spatial …

The functions of multiple instances (FUMI) approach for learning target and nontarget
signatures is introduced. FUMI is a generalization of the multiple-instance learning (MIL) …

Imaging spectroscopy refers to methods for identifying materials in a scene using cameras
that digitize light into hundreds of spectral bands. Each pixel in these images consists of …

Hyperspectral unmixing estimates the proportions of materials represented within a spectral
signature. The over whelming majority of hyperspectral unmixing algorithms are based …