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Fast hyperspectral unmixing in presence of sparse multiple scattering nonlinearities

Halimi, Abderrahim and Bioucas Dias, José and Dobigeon, Nicolas and Buller, Gerald S. and Mclaughlin, Stephen Fast hyperspectral unmixing in presence of sparse multiple scattering nonlinearities. (2017) In: 42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), 5 March 2017 - 9 March 2017 (New Orleans, United States).

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Official URL: https://doi.org/10.1109/ICASSP.2017.7952729

Abstract

This paper presents a novel nonlinear hyperspectral mixture model and its associated supervised unmixing algorithm. The model assumes a linear mixing model corrupted by an additive term which accounts for multiple scattering nonlinearities (NL). The proposed model generalizes bilinear models by taking into account higher order interaction terms. The inference of the abundances and nonlinearity coefficients of this model is formulated as a convex optimization problem suitable for fast estimation algorithms. This formulation accounts for constraints such as the sum-to-one and nonnegativity of the abundances, the non-negativity of the nonlinearity coefficients, and the spatial sparseness of the residuals. The resulting convex problem is solved using the alternating direction method of multipliers (ADMM) whose convergence is ensured theoretically. The proposed mixture model and its unmixing algorithm are validated on both synthetic and real images showing competitive results regarding the quality of the inference and the computational complexity when compared to the state-of-the-art algorithms.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org This papers appears in Proceedings of ICASSP 2017. Electronic ISBN: 978-1-5090-4117-6 Electronic ISSN: 2379-190X The original PDF of the article can be found at: http://ieeexplore.ieee.org/document/7952729/ Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
HAL Id:hal-01757349
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Heriot-Watt University (UNITED KINGDOM)
Other partners > Instituto de Telecomunicações - IT (PORTUGAL)
Other partners > Universidade de Lisboa - ULisboa (PORTUGAL)
Laboratory name:
Funders:
EPSRC Grants EP/J015180/1, EP/N003446/1, EP/K015338/1 - Portuguese Science and Technology
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Deposited By: IRIT IRIT
Deposited On:21 Mar 2018 09:44

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