P172 Seismic Amplitude Recovery with Curvelets P.M. Moghaddam* (University of British Columbia Vancouver) F.H. Herrmann (University of British Columbia Vancouver) & C.S. Stolk (University of Twente Enschede) SUMMARY A non-linear singularity-preserving solution to the least-squares seismic imaging problem with sparseness and continuity constraints is proposed. The applied formalism explores curvelets as a directional frame that by their sparsity on the image and their invariance under the imaging operators allows for a stable recovery of the amplitudes. Our method is based on the estimation of the normal operator in the form of an 'eigenvalue' decompsoition with curvelets as the 'eigenvectors'. Subsequently


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