The ONERA RAMSES SAR system

Dubois-Fernandez, Pascale; Plessis, Olivier Ruault du; Coz, D. Le; Dupas, J.; Vaizan, Bernard; Dupuis, Xavier; Cantalloube, Hubert; Coulombeix, Colette; Titin-Schnaider, C.; Dreuillet, Philippe; Boutry, J. M.; Canny, J.P.; Kaisersmertz, L.; Peyret, J.; Martineau, Ph.; Chanteclerc, Martine; Pastore, L.; Bruyant, Jean-Paul

doi:10.1109/igarss.2002.1026233

Cited by 27 publications

(16 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The SAR image shown in Fig. 9a is an extract of a single look high resolution intensity SAR image of an urban area acquired by the Onera SAR airborne sensor RAMSES (Dubois-Fernandez et al, 2002). Since this image presents important textures and strong reflectors, the PDF in each region is described by a Fisher PDF (Tison et al, 2004).…”

Section: Illustration Of the Results With Real Imagesmentioning

confidence: 99%

Smooth contour coding with minimal description length active grid segmentation techniques

Galland¹,

Jaegler²,

Allain³

et al. 2011

Pattern Recognition Letters

View full text Add to dashboard Cite

Section: Illustration Of the Results With Real Imagesmentioning

confidence: 99%

Smooth contour coding with minimal description length active grid segmentation techniques

Galland¹,

Jaegler²,

Allain³

et al. 2011

Pattern Recognition Letters

View full text Add to dashboard Cite

“…In this section, we present partitions on real PolInSAR images. For this purpose, we consider two Office National d'Etudes et Recherches Aérospatiales (ONERA) RAMSES SAR [31] data sets acquired in P-and X-bands. The first one is a RAMSES X-band image acquired in March 2002 over the Institut National de Recherche Agronomique (INRA) 1 site of Avignon.…”

Section: Applications Of the Statistical Active Gridmentioning

confidence: 99%

Polarimetric and Interferometric SAR Image Partition Into Statistically Homogeneous Regions Based on the Minimization of the Stochastic Complexity

Mitard

Goudail

Dupuis

et al. 2007

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

In this paper, we show that polarimetric and interferometric SAR (PolInSAR) images can be efficiently partitioned into homogeneous regions with a statistical technique based on minimization of a parameter-free criterion. This technique consists of finding a polygonal partition of the image that minimizes the stochastic complexity, assuming that the image is made of a tessellation of statistically homogeneous regions. The obtained results demonstrate that a global partition in statistically homogeneous regions of PolInSAR images can provide better results than a partition based on a single characteristic such as polarimetry or interferometry only.Index Terms-Image segmentation, polarimetric interferometry, SAR interferometry, SAR polarimetry, synthetic aperture radar (SAR).

show abstract

“…Fully polarimetric X-band radar data were acquired by the airborne RAMSES (Radar Aéroporté Multi-Spectral d'Etude des Signatures) SAR (multi-spectral airborne data for signature study) (Dubois et al 2002) from the French Aerospace Research Center (ONERA) on 20 March 2002 over a study site near Avignon (southern France, longitude 4 ‡53' E and latitude 43 ‡55' N). An image of about 1.8 km wide and 5.2 km long was acquired with incidence angles ranging from 13 ‡ to 36 ‡.…”

Section: Datasetmentioning

confidence: 99%

Discrimination potential of X-band polarimetric SAR data

Baghdadi

Holah

Dubois-Fernandez

et al. 2004

International Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

In anticipation of X-band polarimetric Synthetic Aperture Radar (SAR) data from future sensors, we investigated the potential of X-band fully polarimetric data for discriminating between the principal classes present in a study site near Avignon, France. Decomposition and analysis techniques have been applied to a dataset acquired by the ONERA airborne RAMSES (Radar Aéroporté Multi-Spectral d'Etude des Signatures) SAR. Results show that Xband provides some discrimination capability. The polarimetric parameters, entropy and " a a-angle, show clearly that these signature classes are grouped into five clusters corresponding to physical scattering characteristics. The introduction of the anisotropy parameter does not increase our ability to distinguish between different classes whose clusters are in the same entropy=" a a-angle zone. The correlation observed between the radar signal and the surface roughness over bare soils is very low.

show abstract

The ONERA RAMSES SAR system

Cited by 27 publications

References 0 publications

Smooth contour coding with minimal description length active grid segmentation techniques

Smooth contour coding with minimal description length active grid segmentation techniques

Polarimetric and Interferometric SAR Image Partition Into Statistically Homogeneous Regions Based on the Minimization of the Stochastic Complexity

Discrimination potential of X-band polarimetric SAR data

Contact Info

Product

Resources

About