Curvelet-domain least-squares migration with sparseness constraints
| Title | Curvelet-domain least-squares migration with sparseness constraints |
| Publication Type | Conference |
| Year of Publication | 2004 |
| Authors | Felix J. Herrmann, Peyman P. Moghaddam |
| Conference Name | EAGE Annual Conference Proceedings |
| Month | 06 |
| Keywords | EAGE, Presentation, SLIM |
| Abstract | A non-linear edge-preserving solution to the least-squares migration problem with sparseness constraints is introduced. The applied formalism explores Curvelets as basis functions that, by virtue of their sparseness and locality, not only allow for a reduction of the dimensionality of the imaging problem but which also naturally lead to a non-linear solution with significantly improved signal-to-noise ratio. Additional conditions on the image are imposed by solving a constrained optimization problem on the estimated Curvelet coefficients initialized by thresholding. This optimization is designed to also restore the amplitudes by (approximately) inverting the normal operator, which is like-wise the (de)-migration operators, almost diagonalized by the Curvelet transform. |
| URL | https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2004/Herrmann04EAGEcdl/Herrmann04EAGEcdl.pdf |
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| Citation Key | herrmann2004EAGEcdl |