DocumentCode :
3524140
Title :
Sparse decomposition of two dimensional signals
Author :
Ghaffari, Aboozar ; Babaie-Zadeh, Massoud ; Jutten, Christian
Author_Institution :
Electr. Eng. Dept., Sharif Univ. of Technol., Tehran
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
3157
Lastpage :
3160
Abstract :
In this paper, we consider sparse decomposition (SD) of two-dimensional (2D) signals on overcomplete dictionaries with separable atoms. Although, this problem can be solved by converting it to the SD of one-dimensional (1D) signals, this approach requires a tremendous amount of memory and computational cost. Moreover, the uniqueness constraint obtained by this approach is too restricted. Then in the paper, we present an algorithm to be used directly for sparse decomposition of 2D signals on dictionaries with separable atoms. Moreover, we will state another uniqueness constraint for this class of decomposition. Our algorithm is obtained by modifying the Smoothed L0 (SL0) algorithm, and hence we call it two-dimensional SL0 (2D-SL0).
Keywords :
image coding; sparse matrices; compressive sensing; image coding; sparse coding; sparse decomposition; sparse representation; Computational efficiency; Dictionaries; Discrete Fourier transforms; Image coding; Matching pursuit algorithms; Matrix decomposition; Signal processing algorithms; Signal resolution; Sparks; Vectors; Compressive Sensing; Image Coding; Sparse Coding; Sparse Decomposition; Sparse Representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4960294
Filename :
4960294
Link To Document :
بازگشت