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Curvelet-based non-linear adaptive subtraction with sparseness constraints

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Title: Curvelet-based non-linear adaptive subtraction with sparseness constraints
Author: Herrmann, Felix J.; Moghaddam, Peyman P.
Subject Keywords curvelets;contourlets;non-linear adaptive subtraction;sparseness constraints
Issue Date: 2004
Publicly Available in cIRcle 2008-03-26
Publisher Society of Exploration Geophysicists
Citation: Herrmann, Felix J., Moghaddam, Peyman P. 2004. Curvelet-based non-linear adaptive subtraction with sparseness constraints. SEG 74th Annual Meeting and Exposition.
Abstract: In this paper an overview is given on the application of directional basis functions, known under the name Curvelets/Contourlets, to various aspects of seismic processing and imaging, which involve adaptive subtraction. Key concepts in the approach are the use of (i) directional basis functions that localize in both domains (e.g. space and angle); (ii) non-linear estimation, which corresponds to localized muting on the coefficients, possibly supplemented by constrained optimization. We will discuss applications that include multiple, ground-roll removal and migration denoising.
Affiliation: Science, Faculty ofEarth and Ocean Sciences, Department of
URI: http://hdl.handle.net/2429/611
Peer Review Status: Unreviewed
Scholarly Level: Faculty

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