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Communication Dans Un Congrès Année : 2012

Detecting nonlinear mixtures in hyperspectral images

Résumé

This paper presents a new detector for identifying nonlinear mixtures in hyperspectral images. The proposed detector relies on a nonlinear mixing model that approximates the pixel reflectance as a nonlinear combination of pure spectral components contaminated by an additive white Gaussian noise. The parameters involved in the resulting model are estimated using subgradient-based least squares method. A generalized likelihood ratio test is then proposed to decide whether a given pixel results from the commonly used linear mixing model or from a more general nonlinear mixture. The performance of the detection strategy is evaluated thanks to simulations conducted on synthetic data.
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Dates et versions

hal-04240686 , version 1 (13-10-2023)

Identifiants

Citer

Yoann Altmann, Nicolas Dobigeon, Jean-Yves Tourneret. Detecting nonlinear mixtures in hyperspectral images. 4th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2012), IEEE, Jun 2012, Shangai, China. pp.(electronic medium), ⟨10.1109/WHISPERS.2012.6874285⟩. ⟨hal-04240686⟩
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