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Recent developments in endmember extraction and spectral unmixing (2011)
| Venue: | of Advances in Signal Processing and Exploitation Techniques |
| Citations: | 5 - 0 self |
BibTeX
@INPROCEEDINGS{Plaza11recentdevelopments,
author = {Antonio Plaza and Gabriel Martín and Javier Plaza and Maciel Zortea and Sergio Sánchez and A. Plaza and G. Martín and J. Plaza and S. Sánchez and G. Martín and J. Plaza and S. Sánchez and M. Zortea},
title = {Recent developments in endmember extraction and spectral unmixing},
booktitle = {of Advances in Signal Processing and Exploitation Techniques},
year = {2011},
pages = {235--267},
publisher = {Springer}
}
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Abstract
Abstract Spectral unmixing is an important task for remotely sensed hyper-spectral data exploitation. The spectral signatures collected in natural environ-ments are invariably a mixture of the pure signatures of the various materials found within the spatial extent of the ground instantaneous field view of the imaging instrument. Spectral unmixing aims at inferring such pure spectral signatures, called endmembers, and the material fractions, called fractional abundances, at each pixel of the scene. In this chapter, we provide an overview of existing techniques for spectral unmixing and endmember extraction, with par-ticular attention paid to recent advances in the field such as the incorporation of spatial information into the endmember searching process, or the use of nonlinear mixture models for fractional abundance characterization. In order to substantiate the methods presented throughout the chapter, highly representative hyperspectral scenes obtained by different imaging spectrometers are used to provide a quan-titative and comparative algorithm assessment. To address the computational requirements introduced by hyperspectral imaging algorithms, the chapter also
