Split convex minimization algorithm for signal recovery

Author

Combettes, Patrick L. ; Pesquet, Jean-Christophe

Author_Institution

Lab. Jacques-Louis Lions, UPMC Univ. Paris 06, Paris

fYear

2009

fDate

19-24 April 2009

Firstpage

685

Lastpage

688

Abstract

A broad range of signal recovery problems can be abstracted into the problem of minimizing the sum of several convex functions in a Hilbert space. We propose a proximal decomposition algorithm which, under mild conditions, provides a solution to such a problem. A significant improvement over the methods currently in use in the area of signal recovery is that it is not limited to two nondifferentiable functions. An application to image restoration is demonstrated.

Keywords

Hilbert spaces; image restoration; Hilbert space; convex functions; image restoration; nondifferentiable functions; proximal decomposition algorithm; signal recovery; split convex minimization algorithm; Convergence; Data acquisition; Hilbert space; Image restoration; Inverse problems; Minimization methods; Optimization methods; Parallel algorithms; Signal restoration; Wavelet transforms; convex optimization methods; inverse problems; parallel algorithm; signal restoration; variational methods; wavelet transforms;

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.2009.4959676

Filename

4959676