We present a new technique for the compression of remote sensing hyperspectral images based on wavelet transform and zerotree coding of coefficients. In order to improve encoding efficiency, the image is first segmented in a small number of regions with homogeneous texture. Then, a shape adaptive wavelet transform is carried out on each region, and the resulting coefficients are finally encoded by a shape adaptive version of SPIHT. Thanks to the segmentation map (sent as a side information) region boundaries are faithfully preserved, and selective encoding strategies can be easily implemented. In addition, by-now homogeneous region textures can be more efficiently encoded.
Region-oriented compression of multispectral images by shape-adaptive wavelet transform and SPIHT / Cagnazzo, Marco; Poggi, Giovanni; Verdoliva, Luisa; A., Zinicola. - STAMPA. - 4:(2004), pp. 2459-2462. (Intervento presentato al convegno IEEE International Conference on Image Processing tenutosi a Singapore nel ottobre 2004).
Region-oriented compression of multispectral images by shape-adaptive wavelet transform and SPIHT
CAGNAZZO, MARCO;POGGI, GIOVANNI;VERDOLIVA, LUISA;
2004
Abstract
We present a new technique for the compression of remote sensing hyperspectral images based on wavelet transform and zerotree coding of coefficients. In order to improve encoding efficiency, the image is first segmented in a small number of regions with homogeneous texture. Then, a shape adaptive wavelet transform is carried out on each region, and the resulting coefficients are finally encoded by a shape adaptive version of SPIHT. Thanks to the segmentation map (sent as a side information) region boundaries are faithfully preserved, and selective encoding strategies can be easily implemented. In addition, by-now homogeneous region textures can be more efficiently encoded.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
