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Sparse Deconvolution of Seismic Data with A Regularized Norm Ratio.

A. Repetti, M. Q. Pham, L. Duval, E. Chouzenoux, et J.-C. Pesquet.

ICIAM 2015,
Beijing, China, 10-14 Août 2015.

Sparse blind seismic deconvolution aims at jointly estimating an unknown sparse signal (reflectivity) and an unknown impulse response (seismic wavelet). The main difficulty stems from the non-uniqueness of the solutions. They may be regularized by sparsity enforcing norm ratios (Gray, 1978) which are non convex. In this work, we propose an alternating preconditioned method, based on forward-backward iterations, to solve this type of problem, involving a regularized norm ratio, assorted with theoretical convergence results.

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Contact

Biomedical and Astronomical Signal Processing group
Institute of Sensors, Signals and Systems
Heriot-Watt University
Edinburgh EH14 4AS
Scotland UK

mail: A.Repetti@hw.ac.uk



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