Abstract- The region-based description of multispectral images enables important high-level tasks such as data mining and retrieval, and region-of-interest selection. In order to obtain an efficient representation of such images we resort to adaptive transform coding techniques. Such techniques, however, require a considerable information overhead, which must be carefully managed to obtain a satisfactory rate-distortion performance. In this work we develop several region based coding schemes and compare them with conventional (non-adaptive) and class-based schemes, so as to single out the rate-distortion gains/losses of this approach.
Adaptive region-based compression of multispectral images / Cagnazzo, Marco; Gaetano, Raffaele; Parrilli, Sara; Verdoliva, Luisa. - STAMPA. - (2006), pp. 3249-3252. (Intervento presentato al convegno IEEE International Conference on Image Processing tenutosi a Atlanta (USA) nel ottobre 2006).
Adaptive region-based compression of multispectral images
CAGNAZZO, MARCO;GAETANO, RAFFAELE;PARRILLI, SARA;VERDOLIVA, LUISA
2006
Abstract
Abstract- The region-based description of multispectral images enables important high-level tasks such as data mining and retrieval, and region-of-interest selection. In order to obtain an efficient representation of such images we resort to adaptive transform coding techniques. Such techniques, however, require a considerable information overhead, which must be carefully managed to obtain a satisfactory rate-distortion performance. In this work we develop several region based coding schemes and compare them with conventional (non-adaptive) and class-based schemes, so as to single out the rate-distortion gains/losses of this approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.