Curvelet reconstruction with sparsity-promoting inversion:successes and challenges

Curvelet reconstruction with sparsity-promoting inversion:successes and challenges Gilles Hennenfent (Seismic Laboratory for Imaging and Modeling Department of Earth and Ocean Sciences The University of British Columbia) and Felix J. Herrmann (Seismic Laboratory for Imaging and Modeling Department of Earth and Ocean Sciences The University of British Columbia) SUMMARY____________________________________________________________ In this overview of the recent Curvelet Reconstruction with Sparsity-promoting Inversion (CRSI) method we present our latest 2-D and 3-D interpolation results on both synthetic and real datasets. We compare these results to interpolated data using other existing methods. Finally we discuss the challenges related to sparsity-promoting solvers for the large-scale problems