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Proceedings Paper

The use of levelable regularization functions for MRF restoration of SAR images while preserving reflectivity
Author(s): Jérôme Darbon; Marc Sigelle; Florence Tupin
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Paper Abstract

It is well-known that Total Variation (TV) minimization with L2 data fidelity terms (which corresponds to white Gaussian additive noise) yields a restored image which presents some loss of contrast. The same behavior occurs for TV models with non-convex data fidelity terms that represent speckle noise. In this note we propose a new approach to cope with the restoration of Synthetic Aperture Radar images while preserving the contrast.

Paper Details

Date Published: 28 February 2007
PDF: 12 pages
Proc. SPIE 6498, Computational Imaging V, 64980T (28 February 2007); doi: 10.1117/12.698183
Show Author Affiliations
Jérôme Darbon, Univ. of California, Los Angeles (United States)
EPITA (France)
Marc Sigelle, École Nationale Supérieure des Télécommunications (France)
Florence Tupin, École Nationale Supérieure des Télécommunications (France)


Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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