Difference between revisions of "Publications/darbon.07.ei"
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{{Publication |
{{Publication |
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| date = 2006-09-30 |
| date = 2006-09-30 |
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| authors = Jérôme Darbon, Marc Sigelle, Florence Tupin |
| authors = Jérôme Darbon, Marc Sigelle, Florence Tupin |
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| booktitle = Proceedings of the 19th Symposium SPIE on Electronic Imaging |
| booktitle = Proceedings of the 19th Symposium SPIE on Electronic Imaging |
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| address = San Jose, CA, USA |
| address = San Jose, CA, USA |
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+ | | lrdeprojects = Olena |
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| 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. |
| 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. |
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| lrdekeywords = Image |
| lrdekeywords = Image |
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address = <nowiki>{</nowiki>San Jose, CA, USA<nowiki>}</nowiki>, |
address = <nowiki>{</nowiki>San Jose, CA, USA<nowiki>}</nowiki>, |
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month = jan, |
month = jan, |
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| − | project = <nowiki>{</nowiki>Image<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>It is well-known that Total Variation (TV) minimization |
abstract = <nowiki>{</nowiki>It is well-known that Total Variation (TV) minimization |
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with L2 data fidelity terms (which corresponds to white |
with L2 data fidelity terms (which corresponds to white |
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Latest revision as of 15:07, 22 February 2017
- 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.}
}