Wei, Qi and Chen, Marcus and Tourneret, Jean-Yves and Godsill, Simon
Unsupervised nonlinear spectral unmixing based on a multilinear mixing model.
(2017)
IEEE Transactions on Geoscience and Remote Sensing, 55 (8). 4534-4544. ISSN 0196-2892
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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 2MB |
Official URL: http://dx.doi.org/10.1109/TGRS.2017.2693366
Abstract
In the community of remote sensing, nonlinear mixture models have recently received particular attention in hyperspectral image processing. In this paper, we present a novel nonlinear spectral unmixing method following the recent multilinear mixing model of Heylen and Scheunders, which includes an infinite number of terms related to interactions between different endmembers. The proposed unmixing method is unsupervised in the sense that the endmembers are estimated jointly with the abundances and other parameters of interest, i.e., the transition probability of undergoing further interactions. Nonnegativity and sum-to-one constraints are imposed on abun- dances while only nonnegativity is considered for endmembers. The resulting unmixing problem is formulated as a constrained nonlinear optimization problem, which is solved by a block coordinate descent strategy, consisting of updating the end- members, abundances, and transition probability iteratively. The proposed method is evaluated and compared with existing linear and nonlinear unmixing methods for both synthetic and real hyperspectral data sets acquired by the airborne visible/infrared imaging spectrometer sensor. The advantage of using nonlinear unmixing as opposed to linear unmixing is clearly shown in these examples.
Item Type: | Article |
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Additional Information: | Thanks to IEEE editor.The original PDF of the article can be found at : http://ieeexplore.ieee.org/document/7933976/ |
HAL Id: | hal-01681001 |
Audience (journal): | International peer-reviewed journal |
Uncontrolled Keywords: | |
Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Other partners > Duke University (USA) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) Other partners > University of Cambridge (UNITED KINGDOM) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE) Other partners > DSO National Laboratories - DSO (SINGAPORE) |
Laboratory name: | |
Funders: | R. Heylen |
Statistics: | download |
Deposited On: | 11 Jan 2018 10:35 |
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