Recent results in curvelet-based primary-multiple separation

TitleRecent results in curvelet-based primary-multiple separation
Publication TypeConference
Year of Publication2008
AuthorsDeli Wang, Rayan Saab, Ozgur Yilmaz, Felix J. Herrmann
Conference NameSINBAD 2008
KeywordsPresentation, SINBAD, SLIM

We present a nonlinear curvelet-based sparsity-promoting formulation for the primary-multiple separation problem. We show that these coherent signal components can be separated robustly by explicitly exploiting the locality of curvelets in phase space (space-spatial frequency plane) and their ability to compress data volumes that contain wavefronts. This work is an extension of earlier results and the presented algorithms are shown to be stable under noise and moderately erroneous multiple predictions.

Citation Keywang2008SINBADrri