COMPRESSED SENSING SIGNAL RECOVERY VIA A* ORTHOGONAL MATCHING PURSUIT
Compressed Sensing: Theory and Methods
Přednášející: Nazim Burak Karahanoglu, Autoři: Nazim Burak Karahanoglu, TUBITAK - BILGEM, Turkey; Hakan Erdogan, Sabanci University, Turkey
Reconstruction of sparse signals acquired in reduced dimensions requires the solution with minimum l0 norm. As solving the l0 minimization directly is unpractical, a number of algorithms have appeared for finding an indirect solution. A semi-greedy approach, A* Orthogonal Matching Pursuit (A*OMP), is proposed in [1] where the solution is searched on several paths of a search tree. Paths of the tree are evaluated and extended according to some cost function, for which novel dynamic auxiliary cost functions are suggested. This paper describes the A*OMP algorithm and the proposed cost functions briefly. The novel dynamic auxiliary cost functions are shown to provide improved results as compared to a conventional choice. Reconstruction performance is illustrated on both synthetically generated data and real images, which show that the proposed scheme outperforms well-known CS reconstruction methods.
Informace o přednášce
| Nahráno: | 2011-05-26 14:05 - 14:25, Club B |
|---|---|
| Přidáno: | 18. 6. 2011 15:22 |
| Počet zhlédnutí: | 85 |
| Rozlišení videa: | 1024x576 px, 512x288 px |
| Délka videa: | 0:19:27 |
| Audio stopa: | MP3 [6.57 MB], 0:19:27 |
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