@inproceedings{c9f72534069d487c9262e31df2ec863f,
title = "Nonlinear unmixing of vegetated areas: A model comparison based on simulated and real hyperspectral data",
abstract = "When analyzing remote sensing hyperspectral images, numerous works dealing with spectral unmixing assume the pixels result from linear combinations of the endmember signatures. However, this assumption cannot be fulfilled, in particular when considering images acquired over vegetated areas. As a consequence, several nonlinear mixing models have been recently derived to take various nonlinear effects into account when unmixing hyperspectral data. Unfortunately, these models have been empirically proposed and without thorough validation. This paper attempts to fill this gap by taking advantage of two sets of real and physical-based simulated data. The accuracy of various linear and nonlinear models and the corresponding unmixing algorithms is evaluated with respect to their ability of fitting the sensed pixels and of providing accurate estimates of the abundances.",
keywords = "Hyperspectral imagery, nonlinear spectral mixtures, ray tracing, spectral unmixing, vegetated areas",
author = "Nicolas Dobigeon and Laurent Tits and Ben Somers and Yoann Altmann and Pol Coppin",
year = "2017",
month = oct,
day = "26",
doi = "10.1109/WHISPERS.2014.8077629",
language = "English",
series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",
publisher = "IEEE",
booktitle = "2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)",
address = "United States",
note = "6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 2014, WHISPERS 2014 ; Conference date: 24-06-2014 Through 27-06-2014",
}