A Comparison of Nonlinear Mixing Models for Vegetated Areas Using Simulated and Real Hyperspectral Data - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Année : 2014

A Comparison of Nonlinear Mixing Models for Vegetated Areas Using Simulated and Real Hyperspectral Data

Résumé

Abstract--Spectral unmixing (SU) is a crucial processing step when analyzing hyperspectral data. In such analysis, most of the work in the literature relies on the widely acknowledged linear mixing model to describe the observed pixels. Unfortunately, this model has been shown to be of limited interest for specific scenes, in particular when acquired over vegetated areas. Consequently, in the past few years, several nonlinear mixing models have been introduced to take nonlinear effects into account while performing SU. These models have been proposed empirically, however, without any thorough validation. In this paper, the authors take advantage of two sets of real and physical-based simulated data to validate the accuracy of various nonlinear models in vegetated areas. These physics-based models, and their corresponding unmixing algorithms, are evaluated with respect to their ability of fitting the measured spectra and providing an accurate estimation of the abundance coefficients, considered as the spatial distribution of the materials in each pixel.
Fichier principal
Vignette du fichier
Dobigeon_11938.pdf (1.91 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01056556 , version 1 (20-08-2014)

Identifiants

Citer

Nicolas Dobigeon, Laurent Tits, Ben Somers, Yoann Altmann, Pol Coppin. A Comparison of Nonlinear Mixing Models for Vegetated Areas Using Simulated and Real Hyperspectral Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, vol. 7, pp. 1869-1878. ⟨10.1109/JSTARS.2014.2328872⟩. ⟨hal-01056556⟩
87 Consultations
243 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More