Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Paper
28 February 2007 The use of levelable regularization functions for MRF restoration of SAR images while preserving reflectivity
Jérôme Darbon, Marc Sigelle, Florence Tupin
Author Affiliations +
Proceedings Volume 6498, Computational Imaging V; 64980T (2007) https://doi.org/10.1117/12.698183
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jérôme Darbon, Marc Sigelle, and Florence Tupin "The use of levelable regularization functions for MRF restoration of SAR images while preserving reflectivity", Proc. SPIE 6498, Computational Imaging V, 64980T (28 February 2007); https://doi.org/10.1117/12.698183
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Magnetorheological finishing

Synthetic aperture radar

Reflectivity

Speckle

Data modeling

Denoising

Image denoising

Back to Top