DocumentCode :
1682296
Title :
Joint singular value decomposition - a new tool for separable representation of images
Author :
Pesquet-Popescu, Béatrice ; Pesquet, Jean-Christophe ; Petropulu, Athina P.
Author_Institution :
Dept. Signal & Image Process., ENST, Paris, France
Volume :
2
fYear :
2001
Firstpage :
569
Abstract :
We propose a separable decomposition approximating the Karhunen-Loeve transform for random fields. We show that this problem is related to a joint singular value decomposition of a set of matrices and we provide an efficient algorithm to compute it. Finally, we illustrate the interest of this new tool for image representation and approximation
Keywords :
Karhunen-Loeve transforms; approximation theory; image representation; random processes; singular value decomposition; JSVD; Karhunen-Loeve transform; efficient algorithm; image approximation; joint singular value decomposition; matrices; random fields; separable decomposition approximation; separable image representation; simulation results; Eigenvalues and eigenfunctions; Image analysis; Image coding; Image processing; Image representation; Karhunen-Loeve transforms; Matrix decomposition; Pattern recognition; Signal processing; Singular value decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.958556
Filename :
958556
Link To Document :
بازگشت