Título:
SMOS images restoration from L1A data : a sparsity-based variational approach
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Autor:
Preciozzi, Javier
Musé, Pablo
Almansa, Andrés
Durand, Sylvain
Khazaal, Ali
Rougé, Bernard
Musé, Pablo
Almansa, Andrés
Durand, Sylvain
Khazaal, Ali
Rougé, Bernard
Tutor:
Tipo de documento:
Ponencia
Editor:
Palabras clave:
SMOS
MIRAS
RFI
Non-differentiable
Convex optimization
Total variation minimization
MIRAS
RFI
Non-differentiable
Convex optimization
Total variation minimization
Descriptores:
Procesamiento de Señales
Año de publicación:
2014
Contenido:
Resumen:
Data degradation by radio frequency interferences (RFI) is one of the major challenges that SMOS and other interferometers radiometers missions have to face. Although a great number of the illegal emitters were turned off since the mission was launched, not all of the sources were completely removed. Moreover, the data obtained previously is already corrupted by these RFI. Thus, the recovery of brightness temperature from corrupted data by image restoration techniques is of major interest. In this work we propose a variational approach to recover a super-resolved, denoised brightness temperature map based on two spatial components: an image uthat models the brightness temperature and an image o modeling the RFI. The approach is totally new to our knowledge, in the sense that it is directly and exclusively based on the visibilities (L1a data), and thus can also be considered as an alternative to other brightness temperature recovery methods.
Descripción:
Trabajo aceptado en Geoscience and Remote Sensing Symposium, Quebec, Canada, 13-18 jul., 2014
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Citación:
Freciozzi, J, Musé, P, Almansa, A, Durand, S, Khazaal, A, Rougé, B, "SMOS images restoration from L1A data : a sparsity-based variational approach" Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Quebec, Canada, 13-18 jul, 2014, pp. 2487-2490, doi: 10.1109/IGARSS.2014.6946977.
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Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Tratamiento de Imágenes
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| SMOS.pdf | — | 1.36 MB | Adobe PDF |