Title :
Hyperspectral image compression through spectral clustering
Author :
Siala, K. ; Benazza-Benyahia, A.
Author_Institution :
Departement de Mathematques Appliquees, Signal et Commun., Cite Technol. des Commun. de Tunis, Ariana, Tunisia
Abstract :
In this paper, we are interested in coding exactly and gradually hyperspectral image data. To this purpose, vector lifting schemes (VLS) are retained since they take into account the spatial and spectral redundancies in a multiresolution way. However, the high value of the number of components (some hundreds) prevents us applying directly the VLS, due to the tremendous operational complexity. Our contribution consists of a specific preprocessing of the hyperspectral images to make possible the use of VLS at the further stage. Experiments performed on AVIRIS images indicate the outperformance of the proposed method w.r.t. to the state-of-art coders.
Keywords :
geophysical signal processing; image coding; pattern clustering; remote sensing; vector quantisation; hyperspectral image compression; hyperspectral image data; image coding; spatial redundancies; spectral clustering; spectral redundancies; vector lifting schemes; Communications technology; High-resolution imaging; Hyperspectral imaging; Image coding; Image resolution; Monitoring; Optical imaging; Resource management; Spatial resolution; Spectroscopy;
Conference_Titel :
Control, Communications and Signal Processing, 2004. First International Symposium on
Print_ISBN :
0-7803-8379-6
DOI :
10.1109/ISCCSP.2004.1296322