@article {wang2008GEOPbws,
	title = {Bayesian wavefield separation by transform-domain sparsity promotion},
	journal = {Geophysics},
	volume = {73},
	number = {5},
	year = {2008},
	month = {07},
	pages = {1-6},
	abstract = {Successful removal of coherent noise sources greatly determines the quality of seismic imaging. Major advances were made in this direction, e.g., Surface-Related Multiple Elimination (SRME) and interferometric ground-roll removal. Still, moderate phase, timing, amplitude errors and clutter in the predicted signal components can be detrimental. Adopting a Bayesian approach along with the assumption of approximate curvelet-domain independence of the to-be-separated signal components, we construct an iterative algorithm that takes the predictions produced by for example SRME as input and separates these components in a robust fashion. In addition, the proposed algorithm controls the energy mismatch between the separated and predicted components. Such a control, which was lacking in earlier curvelet-domain formulations, produces improved results for primary-multiple separation on both synthetic and real data.},
	keywords = {curvelet transform, Geophysics, Optimization, Processing, SLIM},
	doi = {10.1190/1.2952571},
	url = {http://slim.gatech.edu/Publications/Public/Journals/Geophysics/2008/wang08GEObws/wang08GEObws.pdf},
	html_version = {http://slim.gatech.edu/Publications/Public/Journals/2008/wang08TRbss/paper_html/paper.html},
	author = {Deli Wang and Rayan Saab and Ozgur Yilmaz and Felix J. Herrmann}
}
