The use of levelable regularization functions for MRF restoration of SAR images
From LRDE
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- Authors
- Jérôme Darbon, Marc Sigelle, Florence Tupin
- Where
- Proceedings of the 19th Symposium SPIE on Electronic Imaging
- Place
- San Jose, CA, USA
- Type
- inproceedings
- Projects
- Olena
- Keywords
- Image
- Date
- 2006-09-30
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 TVmodels 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.
Bibtex (lrde.bib)
@InProceedings{ darbon.07.ei, author = {J\'er\^ome Darbon and Marc Sigelle and Florence Tupin}, title = {The use of levelable regularization functions for {MRF} restoration of {SAR} images}, booktitle = {Proceedings of the 19th Symposium SPIE on Electronic Imaging}, year = 2007, address = {San Jose, CA, USA}, month = jan, 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 TVmodels 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.} }