Abstract
This paper discusses a new greedy algorithm for solving the sparse approximation problem over quasi-incoherent 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.
Original language | English (US) |
---|---|
Pages | 37-40 |
Number of pages | 4 |
State | Published - 2003 |
Event | Proceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain Duration: Sep 14 2003 → Sep 17 2003 |
Other
Other | Proceedings: 2003 International Conference on Image Processing, ICIP-2003 |
---|---|
Country/Territory | Spain |
City | Barcelona |
Period | 9/14/03 → 9/17/03 |
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering