. .. Mélange-linéaire-instantané, , vol.8

.. .. Mélange,

. .. Mélanges-non-linéaires,

. .. Mélange-post-non-linéaire,

. .. Mélange-linéaire-quadratique, , p.10

. .. Paramètres-complémentaires, 10 1.3.1 Estimation du nombre de sources

. .. Instantanés, 2 Méthodes basées sur la structure des signaux, Méthodes pour les mélanges linéaires, p.16

. .. Analyse-en-composantes-parcimonieuses,

.. .. Inférence-bayésienne,

.. .. Méthodes, , p.38

. .. Conclusion,

, Chapitre 2

. .. Modèle-du-cube,

. .. Méthodes-de-sas-en-observation-de-la-terre, 53 2.4.1 Panorama des méthodes standard

.. .. Méthodes,

´. .. Etat, , p.59

. .. Analyse-en-composantes-indépendantes, , p.59

.. .. Méthodes,

. .. Analyse-en-composantes-parcimonieuses, 61 2.6 ´ Etude de nos données et choix méthodologiques, p.61

. .. Caractéristiques-des-images-hyperspectrales, , p.62

.. .. Choix,

. .. Conclusion,

. .. Résultats-expérimentaux-sur-données-réelles,

. .. Conclusion,

, Chapitre 4

. , Méthode géométriquè a pixels purs et somme d'abondance non contrainte Sommaire Introduction, p.117

M. .. La-méthode, 118 4.2.1 Estimation de la matrice de mélange

.. .. Méthodes,

. .. Résultats-expérimentaux-sur-données-synthétiques,

. .. Résultats-expérimentaux-sur-données-réelles,

, Chapitre 5

. , Méthode de SAS basée sur l'intersection de sous-espaces Sommaire Introduction

. , Estimation de la matrice de mélange

.. .. Résultats,

. .. Conclusion, 2.1.3 illustrant l'utilisation de l'algorithme NNLS [88] dans notre contexte. En pratique, l'algorithme de SIBIS se résume doncàdonc`doncà : Entrées : X l'ensemble des bandes spectrales observées

, Segmentation du cube de données en régions homogènes :-Parcours de tout l'espace spatial du cube et estimation pour chaque zone Z du nombre de sources actives en utilisant la méthode décrite dans la Section 1.3.1.-Fusion des régions connexes ayant les mêmes sources actives

, Détection des paires de zones ayant une unique source en commun (paires IMS) suivant la relation Eq, vol.7

, Estimation de la colonne de la matrice de mélange associéè a chaque paire IMS :-Résolution du système Eq. (5.13) avec la SVD.-Le paramètre ? ainsi obtenu permet de définir une base de l'intersection des deux zones avec la relation

, Classification des colonnes potentielles précédemment obtenues en L ensembles. Le centre de chaque cluster donne une estimation de chaque colonne de A

, Reconstruction des sources par NNLS avec Eq

, Résultats expérimentaux

, Nous comparons les performances obtenues avec celles obtenues avec la MC-NMF. Dans un second temps, nous appliquons la méthode SIBIS aux données de NGC7023-NW cartographiée par IRS-Spitzer (voir Section 2.6, et plusparticulì erement la Figure 2.9 présentant ces données) et nous comparons les résultats obtenus avec ceux estimés par deux autres méthodes, PourévaluerPourévaluer les performances de SIBIS, nous réalisons deux expériences

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