. Fig, 7 ? Exemple de compression d'image SLC par l'algorithme WP-ECUPQ après transformée bi-orthogonale 9/7 de l'image complexe

. Compression-de-la-scène, Istres" L'image d'Istres de taille 512x512 a été compressée avec des taux de ? = 32 : 1, ? = 16 : 1, ? = 10

. La-transformée-en-ondelettes-et-paquets-d, ondelettes est réalisée à partir de la transformée biorthogonale 9/7 [5] implémentée sous forme de structure "Lifting" [89] [90] [42]. Cette technique de factorisation implémente la transformée bi-orthogonale sous forme d'une suite finie d'étages de filtres de prédiction

. Fig, 1 ? Image d'amplitude extraite d'une zone de la ville d'Istres(512x512). c ONERA

L. Méthodes, W. , and W. , ECUPQ basées sur une représentation en paquets d'ondelettes de la partie réelle et imaginaire de l'image SLC semblent apporter les meilleures performances tous critères confondus. L'hypothèse haut-débit à partir de laquelle nous avons élaboré les algorithmes WECUPQ et WP-ECUPQ semble néanmoins fournir la limitation de cette approche

. Afin, Taubman [95] montre la condition nécessaire et suffisante d'appartenance z ? H est donnée par : ? (z) > 0 et ? (z) > max t>z D(z) ? D(t) R(t) ? R(z) Pour plus de précisions, nous renvoyons le lecteur à [97] sur la preuve de ce théorème. Autrement dit, pour un point z ? Z donné, celui-ci appartient à l'ensemble H si toutes les pentes calculées avec les points t > z sont strictement inférieures à ? (z), Cette condition nécessaire et suffisante garantie ainsi une décroissance monotone du paramètre ?(z)

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