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Compressed sensing signal recovery via A* Orthogonal Matching Pursuit

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2 Author(s)
Karahanoglu, Nazim Burak ; Information Technologies Institute, TUBITAK-BILGEM, Kocaeli, Turkey ; Erdogan, Hakan

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.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on

Date of Conference:

22-27 May 2011