A new region-based algorithm is proposed for the compression of multispectral images. The image is segmented in homogeneous regions, each of which is subject to spectral KLT, spatial shape-adaptive DWT, and SPIHT encoding. We propose to use a dedicated KLT for each region or for each class rather than a single global KLT. Experiments show that the classified KLT guarantees a significant increase in energy compaction, and hence, despite the need to transmit more side information, it provides a valuable performance gain over reference techniques.
Region based compression of multispectral images by classified KLT / Cagnazzo, Marco; Gaetano, Raffaele; Parrilli, Sara; Verdoliva, Luisa. - STAMPA. - (2006), pp. 1001-1005. (Intervento presentato al convegno XIV European Signal Processing Conference tenutosi a Firenze (I) nel settembre 2006).
Region based compression of multispectral images by classified KLT
CAGNAZZO, MARCO;GAETANO, RAFFAELE;PARRILLI, SARA;VERDOLIVA, LUISA
2006
Abstract
A new region-based algorithm is proposed for the compression of multispectral images. The image is segmented in homogeneous regions, each of which is subject to spectral KLT, spatial shape-adaptive DWT, and SPIHT encoding. We propose to use a dedicated KLT for each region or for each class rather than a single global KLT. Experiments show that the classified KLT guarantees a significant increase in energy compaction, and hence, despite the need to transmit more side information, it provides a valuable performance gain over reference techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
