Source separation via SVD-free rank minimization in the hierarchical semi-separable representation
This application is available only in the software release for members of SINBAD consortium.
This software release includes a demonstration of a 2-D over/under blended marine acquisition scenario, and a source separation algorithm based on a SVD-free rank minimization scheme.
Author: Haneet Wason (hwason@eos.ubc.ca)
Date: June, 2014; July, 2016 - parallel version of the code made available.
Contents
Downloading & Dependencies
The code can be found in the SLIM software release under /applications/Acquisition/SourceSeparationLowRankHSS.
The code has been tested with Matlab R2015b. The updated code requires the Parallel Computing Toolbox.
This code uses the following packages, also found in the tools part of the SLIM software release.
- utilities/SPOT-SLIM - object oriented framework for matrix-free linear algebra.
- utilities/SegyMAT - Matlab/Octave toolbox for reading and writing SEG-Y formatted files.
- solvers/GenSPGL1 - Generalized SPGL1.
Running & Parallelism
All the examples and results are produced by the scripts found in this software release under applications/Acquisition/SourceSeparationLowRankHSS/examples/. Start matlab from applications/Acquisition/SourceSeparationLowRankHSS to add the appropriate paths.
To run the scripts follow the instructions in the README file enclosed with the code. The scripts are run in parallel mode.
Examples and results
Examples and results are shown here. Scripts to reproduce the results can be found under /applications/Acquisition/SourceSeparationLowRankHSS/examples.
References
[1] Rajiv Kumar, Haneet Wason, and Felix J. Herrmann [2015]. Source separation for simultaneous towed-streamer marine acquisition --- a compressed sensing approach, Geophysics, vol. 80, pp. WD73-WD88.
[2] Haneet Wason, Rajiv Kumar, Aleksandr Y. Aravkin, and Felix J. Herrmann [2014]. Source separation via SVD-free rank minimization in the hierarchical semi-separable representation, presented at the SEG Conference.
[3] Aleksandr Y. Aravkin, Rajiv Kumar, Hassan Mansour, Ben Recht, and Felix J. Herrmann [2014]. Fast methods for denoising matrix completion formulations, with applications to robust seismic data interpolation, SIAM Journal on Scientific Computing (SISC), vol. 36, pp. S237-S266.
[4] Rajiv Kumar, Hassan Mansour, Aleksandr Y. Aravkin, and Felix J. Herrmann [2013]. Reconstruction of seismic wavefields via low-rank matrix factorization in the hierarchical-separable matrix representation, SEG Technical Program Expanded Abstracts, p. 3628-3633.
Acknowledgements
Thanks to our sponsors and NSERC for their financial support.