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A perturbed linear mixing model accounting for spectral variability

Pierre-Antoine Thouvenin 1 Nicolas Dobigeon 1, 2 Jean-yves Tourneret 3, 2 
1 IRIT-SC - Signal et Communications
IRIT - Institut de recherche en informatique de Toulouse
3 IRIT-MINDS - CoMputational imagINg anD viSion
IRIT - Institut de recherche en informatique de Toulouse
Abstract : Hyperspectral unmixing aims at determining the reference spectral signatures composing a hyperspectral image, their abundance fractions and their number. In practice, the spectral variability of the identified signatures induces significant abundance estimation errors. To address this issue, this paper introduces a new linear mixing model explicitly accounting for this phenomenon. In this setting, the extracted endmembers are interpreted as possibly corrupted versions of the true endmembers. The parameters of this model can be estimated using an optimization algorithm based on the alternating direction method of multipliers. The performance of the proposed unmixing method is evaluated on synthetic and real data.
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Submitted on : Tuesday, September 6, 2016 - 1:30:59 PM
Last modification on : Wednesday, June 1, 2022 - 4:05:04 AM
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  • HAL Id : hal-01360872, version 1
  • OATAO : 15347


Pierre-Antoine Thouvenin, Nicolas Dobigeon, Jean-yves Tourneret. A perturbed linear mixing model accounting for spectral variability. 23rd European Signal and Image Processing Conference (EUSIPCO 2015), Aug 2015, Nice, France. pp. 814-818. ⟨hal-01360872⟩



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