@conference {herrmann2006SINBADsac,
	title = {Sparsity- and continuity-promoting seismic image recovery with curvelets},
	booktitle = {SINBAD 2006},
	year = {2006},
	abstract = {A nonlinear singularity-preserving solution to seismic image recovery with sparseness and continuity constraints is proposed. The method explicitly explores the curvelet transform as a directional frame expansion that, by virtue of its sparsity on seismic images and its invariance under the Hessian of the linearized imaging problem, allows for a stable recovery of the migration amplitudes from noisy data. The method corresponds to a preconditioning that corrects the amplitudes during a post-processing step. The solution is formulated as a nonlinear optimization problem where sparsity in the curvelet domain as well as continuity along the imaged reflectors are jointly promoted. To enhance sparsity, the l1-norm on the curvelet coefficients is minimized while continuity is promoted by minimizing an anisotropic diffusion norm on the image. The performance of the recovery scheme is evaluated with {\textquoteright}wave-equation{\textquoteright} migration code on a synthetic dataset. This is joint work with Peyman Moghaddam.},
	keywords = {Presentation, SINBAD, SLIM},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/SINBAD/2006/herrmann2006SINBADsac/herrmann2006SINBADsac.pdf},
	author = {Felix J. Herrmann}
}
