Descripteur
Vedettes matières IGN > Traitement d'image radar et applications
Traitement d'image radar et applications |
Documents disponibles dans cette catégorie (602)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
Integrated denoising and unwrapping of INSAR phase based on Markov random fields / Runpu Chen in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)
![]()
[article]
Titre : Integrated denoising and unwrapping of INSAR phase based on Markov random fields Type de document : Article/Communication Auteurs : Runpu Chen, Auteur ; Weidong Yu, Auteur ; Robert Wang, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 4473 - 4485 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] champ aléatoire de Markov
[Termes IGN] filtrage du bruit
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] phase
[Termes IGN] reconstruction d'image
[Termes IGN] restauration d'imageRésumé : (Auteur) In the traditional processing flow of interferometric synthetic aperture radar (SAR) technique, the processing of phase is conducted via two separated and successive steps, i.e., phase denoising and phase unwrapping. That is to say, first, wrapped phases without noise are generated, and then, the true phases without 2?-ambiguities are reconstructed (here and in the rest of this paper, true phase refers to the information-induced unwrapped phase without noise). Such separated steps will inevitably bring in extra estimation error because each step has necessary approximations and presumptions which do not always hold. On the contrary, in this paper, we treat phase denoising and unwrapping as a single problem of true phase recovery from observed ones. Following this methodology, an integrated phase denoising and unwrapping algorithm based upon Markov random fields (MRFs) is proposed. Taking a priori knowledge of interferometric phases into account, MRF is used to model the relationship between the elements in the random variable set including both true phases and their observations. After the model is built up, the energy function of this MRF is defined according to the local-independence property inferred from the MRF structure and then minimized to obtain the estimate of the true phase value. In the end of this paper, experiments on simulated and true phase data are conducted, and the comparison with several commonly used unwrapping methods is proposed to verify the efficiency of the proposed MRF algorithm. Numéro de notice : A2013-419 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2268969 En ligne : https://doi.org/10.1109/TGRS.2013.2268969 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32557
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 8 (August 2013) . - pp 4473 - 4485[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013081 RAB Revue Centre de documentation En réserve L003 Disponible Phenomenology of ground scattering in a tropical forest through polarimetric synthetic aperture radar tomography / Mauro Mariotti d'Alessandro in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)
![]()
[article]
Titre : Phenomenology of ground scattering in a tropical forest through polarimetric synthetic aperture radar tomography Type de document : Article/Communication Auteurs : Mauro Mariotti d'Alessandro, Auteur ; Stefano Tebaldini, Auteur ; Fabio Rocca, Auteur Année de publication : 2013 Article en page(s) : pp 4430 - 4437 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande P
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] image radar moirée
[Termes IGN] niveau du sol
[Termes IGN] polarimétrie radar
[Termes IGN] tomographieRésumé : (Auteur) This paper aims at characterizing the scattering mechanisms occurring at the ground level in a tropical forest illuminated by a P-band synthetic aperture radar (SAR). The analysis is carried out based on the multibaseline, fully polarimetric, data set collected by ONERA over Paracou, French Guyana, in the frame of the European space agency campaign TropiSAR. The favorable baseline distribution of this data set results in the possibility of removing most contributions from the vegetation layer by tomographic techniques, thus allowing the generation of a new fully polarimetric single look complex SAR image relative to scattering contributions from the ground level only. Such a ground layer image is then analyzed by considering the variation of its polarimetric signature with respect to terrain local slope and Radar look angle. Two major conclusions are drawn: 1) double bounce scattering from trunk-ground interactions is observed to be the dominant scattering mechanism at the ground level on flat terrains, whereas it rapidly tends to vanish as the topographic slope increases, and 2) the characteristic parameter that rules trunk-ground scattering is not the tree height, but rather the available free path facing the tree, as a result of the presence of nearby trees, undulating topography, or understory preventing double bounce scattering from taking place whenever the ground bounce occurs too far away from the considered tree. The mean free path length resulting from the analysis of this data-set is found to be L ? 7 m. Finally, we discuss how the concept of free path length can be accounted for in simple terms by assuming an equivalent extinction model characterized by a variation along the horizontal dimension. Numéro de notice : A2013-415 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2246573 En ligne : https://doi.org/10.1109/TGRS.2013.2246573 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32553
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 8 (August 2013) . - pp 4430 - 4437[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013081 RAB Revue Centre de documentation En réserve L003 Disponible Retrieval of tropical forest biomass information from ALOS PALSAR data / Mahmudur Rahman in Geocarto international, vol 28 n° 5-6 (August - October 2013)
![]()
[article]
Titre : Retrieval of tropical forest biomass information from ALOS PALSAR data Type de document : Article/Communication Auteurs : Mahmudur Rahman, Auteur ; Josaphat Tetuko Sri Sumantyo, Auteur Année de publication : 2013 Article en page(s) : pp 382 - 403 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] Bangladesh
[Termes IGN] biomasse
[Termes IGN] forêt tropicale
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] régression
[Termes IGN] rétrodiffusionRésumé : (Auteur) Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data from different observation modes were analysed to determine (1) which observation mode most accurately retrieves tropical forest biomass information and (2) whether different modes, when considered together, yield improved results in comparison to identical data-sets analysed independently. We performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh. The coefficient of determination (r 2) was lower or equal to 0.499 (n = 70) when PALSAR data from different observation modes were separately considered, but increased sharply when one class (rubber) is dropped and average backscatter of fine beam single (FBS) and polarimetric (PLR) modes are used in the analysis. The results presented in this article are useful for both regional and global forest biomass inventories and fixing acquisition modes for planned L-band SAR missions. Numéro de notice : A2013-547 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.710652 Date de publication en ligne : 04/09/2012 En ligne : https://doi.org/10.1080/10106049.2012.710652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32683
in Geocarto international > vol 28 n° 5-6 (August - October 2013) . - pp 382 - 403[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2013031 RAB Revue Centre de documentation En réserve L003 Disponible Supervised constrained optimization of Bayesian nonlocal means filter with sigma preselection for despeckling SAR images / Luis Gomez in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)
![]()
[article]
Titre : Supervised constrained optimization of Bayesian nonlocal means filter with sigma preselection for despeckling SAR images Type de document : Article/Communication Auteurs : Luis Gomez, Auteur ; Cristian Munteanu, Auteur ; Maria Buemi, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 4563 - 4575 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] filtre de Bayer
[Termes IGN] filtre de déchatoiement
[Termes IGN] image radar moirée
[Termes IGN] optimisation (mathématiques)
[Termes IGN] varianceRésumé : (Auteur) Speckle reduction is an important problem in synthetic aperture radar (SAR) image analysis. Recent years have seen how Bayesian filters emerge as the natural extension of the nonlocal means filters, providing a general framework to deal with multiplicative (speckle) noise. In this paper, we present an easy-to-use software tool applying an evolutionary algorithm to optimize a Bayesian nonlocal means filter with sigma preselection for denoising SAR images. The desired result is a filtered image having a significative reduction in its variance but preserving the original mean value of the noisy image. A mixed-integer constrained optimization problem is stated and solved with the human intervention, where the user assists the evolutionary algorithm to reduce the noisy image variance under the restriction of keeping the mean value of the noisy SAR image within a predetermined interval of acceptance. We apply the methodology to a set of synthetic and real SAR speckle corrupted images. The results through the evaluation of objective global and local quality criteria show the excellent potential of the proposal. Numéro de notice : A2013-421 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2269866 En ligne : https://doi.org/10.1109/TGRS.2013.2269866 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32559
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 8 (August 2013) . - pp 4563 - 4575[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013081 RAB Revue Centre de documentation En réserve L003 Disponible Texture classification of PolSAR data based on sparse coding of wavelet polarization textons / Chu He in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)
![]()
[article]
Titre : Texture classification of PolSAR data based on sparse coding of wavelet polarization textons Type de document : Article/Communication Auteurs : Chu He, Auteur ; Shuang Li, Auteur ; Zixian Liao, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 4576 - 4590 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image radar moirée
[Termes IGN] ondelette
[Termes IGN] polarimétrie radar
[Termes IGN] polarisation
[Termes IGN] texture d'imageRésumé : (Auteur) This paper presents a frame for classifying polarimetric synthetic aperture radar (PolSAR) data. The frame is based on the combination of wavelet polarization information, textons, and sparse coding. Polarimetric synthesis unites with the discrete wavelet frame to obtain wavelet polarization variance through the calculation of the wavelet variance in the space of polarization states. The K-means cluster algorithm is implemented to cluster the wavelet polarization variance vectors of the training samples for the purpose of constructing a texton dictionary. A patch, in which all the wavelet polarization variance vectors match those in the texton dictionary, is used to obtain a statistical histogram. Sparse coding is applied to describe the histogram feature and generate a new texture feature called sparse coding of a wavelet polarization texton. Finally, support vector machine is used for the classification. All experiments are carried out on five sets of PolSAR data. The experimental results confirm that the proposed method effectively classifies PolSAR data. Numéro de notice : A2013-422 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2236338 En ligne : https://doi.org/10.1109/TGRS.2012.2236338 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32560
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 8 (August 2013) . - pp 4576 - 4590[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013081 RAB Revue Centre de documentation En réserve L003 Disponible An unsupervised classification approach for polarimetric SAR data based on the Chernoff distance for complex Wishart distribution / Mohammed Dabboor in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 2 (July 2013)
PermalinkAnalysis on the resolution of polarimetric radar and performance evaluation of the polarimetric bandwidth extrapolation method / Kei Suwa in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 2 (July 2013)
PermalinkDEM error correction in InSAR time series / Heresh Fattahi in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 2 (July 2013)
PermalinkDenoising atmospheric radar signals using spectral-based subspace method applicable for PBS wind estimation / V.N. Sureshbabu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)
PermalinkFull polarimetric bistatic radar imaging experiments on sets of dielectric cylinders above a conductive circular plate / Sami Bellez in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 2 (July 2013)
PermalinkLeaf area index estimation of boreal and subarctic forests using VV/HH ENVISAT/ASAR data of various swaths / Terhikki Manninen in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)
PermalinkÉlaboration de la cartographie des échos du sol d’un radar météorologique à l’aide du modèle numérique de terrain (SRTM) / Abdenasser Djafri in Revue internationale de géomatique, vol 23 n° 2 (juin - aout 2013)
PermalinkEstimation of glacier ice extinction using long-wavelength airborne Pol-InSAR / Jayanti J. Sharma in IEEE Transactions on geoscience and remote sensing, vol 51 n° 6 Tome 2 (June 2013)
PermalinkForest biomass estimation using texture measurements of high-resolution dual-polarization C-band SAR data / Latifur Rahman Sarker in IEEE Transactions on geoscience and remote sensing, vol 51 n° 6 Tome 1 (June 2013)
PermalinkImproved topographic mapping through high-resolution SAR interferometry with atmospheric effect removal / Mingsheng Liao in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)
Permalink