Title :
Improved sparse approximation over quasiincoherent dictionaries
Author :
Tropp, J.A. ; Gilbert, A.C. ; Muthukrishnan, S. ; Strauss, M.J.
Author_Institution :
Inst. for Comput. Eng. & Sci., Texas Univ., Austin, TX, USA
Abstract :
This paper discusses a new greedy algorithm for solving the sparse approximation problem over quasiincoherent dictionaries. These dictionaries consist of waveforms that are uncorrelated "on average," and they provide a natural generalization of incoherent dictionaries. The algorithm provides strong guarantees on the quality of the approximations it produces, unlike most other methods for sparse approximation. Moreover, very efficient implementations are possible via approximate nearest-neighbor data structures.
Keywords :
algorithm theory; data structures; dictionaries; image processing; iterative methods; sparse matrices; greedy algorithm; image processing; matching pursuit; nearest-neighbor data structures; quasiincoherent dictionary; sparse approximation; Algorithm design and analysis; Approximation algorithms; Costs; Dictionaries; Matching pursuit algorithms; Signal resolution; Wavelet packets;
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7803-7750-8
DOI :
10.1109/ICIP.2003.1246892