Constrained reflect-then-combine methods for unmixing hyperspectral data
Résumé
This paper deals with the linear unmixing problem in hyperspectral data processing, and in particular the estimation of the fractional abundances under sum-to-one and non-negativity constraints. For this purpose, we propose to adapt the reflect-then-combine iterative technique, initially derived by Cimmino. Several strategies are studied in order to handle the constraints, and experimental results are analyzed.
Mots clés
image processing
iterative methods
remote sensing
unmixing hyperspectral data
linear unmixing problem
hyperspectral data processing
reflect-then-combine iterative technique
Convergence
Optimization
Hyperspectral imaging
Mathematical model
Data processing
Estimation
Additives
Constrained optimization
hyperspectral data
unmixing problem
parallel projection
Cimmino's method
| Origine | Fichiers produits par l'(les) auteur(s) |
|---|
Loading...