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Hyperspectral image denoising employing a spectral-spatial adaptive total variation model / Q. Yuan in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)
[article]
Titre : Hyperspectral image denoising employing a spectral-spatial adaptive total variation model Type de document : Article/Communication Auteurs : Q. Yuan, Auteur ; L. Zhang, Auteur ; H. Shen, Auteur Année de publication : 2012 Article en page(s) : pp 3660 - 3677 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] filtrage du bruit
[Termes IGN] image hyperspectrale
[Termes IGN] itération
[Termes IGN] variationRésumé : (Auteur) The amount of noise included in a hyperspectral image limits its application and has a negative impact on hyperspectral image classification, unmixing, target detection, and so on. In hyperspectral images, because the noise intensity in different bands is different, to better suppress the noise in the high-noise-intensity bands and preserve the detailed information in the low-noise-intensity bands, the denoising strength should be adaptively adjusted with the noise intensity in the different bands. Meanwhile, in the same band, there exist different spatial property regions, such as homogeneous regions and edge or texture regions; to better reduce the noise in the homogeneous regions and preserve the edge and texture information, the denoising strength applied to pixels in different spatial property regions should also be different. Therefore, in this paper, we propose a hyperspectral image denoising algorithm employing a spectral-spatial adaptive total variation (TV) model, in which the spectral noise differences and spatial information differences are both considered in the process of noise reduction. To reduce the computational load in the denoising process, the split Bregman iteration algorithm is employed to optimize the spectral-spatial hyperspectral TV model and accelerate the speed of hyperspectral image denoising. A number of experiments illustrate that the proposed approach can satisfactorily realize the spectral-spatial adaptive mechanism in the denoising process, and superior denoising results are produced. Numéro de notice : A2012-523 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2185054 Date de publication en ligne : 07/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2185054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31969
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 10 Tome 1 (October 2012) . - pp 3660 - 3677[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012101A RAB Revue Centre de documentation En réserve L003 Disponible An advanced algorithm for deformation estimation in non-urban areas / K. Goel in ISPRS Journal of photogrammetry and remote sensing, vol 73 (September 2012)
[article]
Titre : An advanced algorithm for deformation estimation in non-urban areas Type de document : Article/Communication Auteurs : K. Goel, Auteur ; Nico Adam, Auteur Année de publication : 2012 Article en page(s) : pp 100 - 110 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] déformation de la croute terrestre
[Termes IGN] filtrage du bruit
[Termes IGN] image radar moirée
[Termes IGN] image TanDEM-X
[Termes IGN] interferométrie différentielle
[Termes IGN] zone ruraleRésumé : (Auteur) This paper presents an advanced differential SAR interferometry stacking algorithm for high resolution deformation monitoring in non-urban areas with a focus on distributed scatterers (DSs). Techniques such as the Small Baseline Subset Algorithm (SBAS) have been proposed for processing DSs. SBAS makes use of small baseline differential interferogram subsets. Singular value decomposition (SVD), i.e. L2 norm minimization is applied to link independent subsets separated by large baselines. However, the interferograms used in SBAS are multilooked using a rectangular window to reduce phase noise caused for instance by temporal decorrelation, resulting in a loss of resolution and the superposition of topography and deformation signals from different objects. Moreover, these have to be individually phase unwrapped and this can be especially difficult in natural terrains. An improved deformation estimation technique is presented here which exploits high resolution SAR data and is suitable for rural areas. The implemented method makes use of small baseline differential interferograms and incorporates an object adaptive spatial phase filtering and residual topography removal for an accurate phase and coherence estimation, while preserving the high resolution provided by modern satellites. This is followed by retrieval of deformation via the SBAS approach, wherein, the phase inversion is performed using an L1 norm minimization which is more robust to the typical phase unwrapping errors encountered in non-urban areas. Meter resolution TerraSAR-X data of an underground gas storage reservoir in Germany is used for demonstrating the effectiveness of this newly developed technique in rural areas. Numéro de notice : A2012-548 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.06.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31994
in ISPRS Journal of photogrammetry and remote sensing > vol 73 (September 2012) . - pp 100 - 110[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012071 SL Revue Centre de documentation Revues en salle Disponible Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification / S. Prasad in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)
[article]
Titre : Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification Type de document : Article/Communication Auteurs : S. Prasad, Auteur ; J. Fowler, Auteur ; L. Bruce, Auteur ; W. Li, Auteur Année de publication : 2012 Article en page(s) : pp 3474 - 3486 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] filtrage du bruit
[Termes IGN] fusion de données
[Termes IGN] image hyperspectrale
[Termes IGN] méthode robuste
[Termes IGN] partitionnement
[Termes IGN] redondance de données
[Termes IGN] transformation en ondelettesRésumé : (Auteur) Hyperspectral imagery comprises high-dimensional reflectance vectors representing the spectral response over a wide range of wavelengths per pixel in the image. The resulting high-dimensional feature spaces often result in statistically ill-conditioned class-conditional distributions. Conventional methods for alleviating this problem typically employ dimensionality reduction such as linear discriminant analysis along with single-classifier systems, yet these methods are suboptimal and lack noise robustness. In contrast, a divide-and-conquer approach is proposed to address the high dimensionality of hyperspectral data for effective and noise-robust classification. Central to the proposed framework is a redundant wavelet transform for representing the data in a feature space amenable to noise-robust multiscale analysis as well as a multiclassifier and decision-fusion system for classification and target recognition in high-dimensional spaces under small-sample-size conditions. The proposed partitioning of this feature space assigns a collection of all coefficients across all scales at a particular spectral wavelength to a dedicated classifier. It is demonstrated that such a partitioning of the feature space for a multiclassifier system yields superior noise performance for classification tasks. Additionally, validation studies with experimental hyperspectral data show that the proposed system significantly outperforms conventional denoising and classification approaches. Numéro de notice : A2012-451 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2185053 Date de publication en ligne : 06/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2185053 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31897
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3474 - 3486[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data / D. Rodrigues Dos Santos in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)
[article]
Titre : A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data Type de document : Article/Communication Auteurs : D. Rodrigues Dos Santos, Auteur ; Antonio Maria Garcia Tommaselli, Auteur ; Q. Dalmolin, Auteur ; E. Aparecido Mitishita, Auteur Année de publication : 2012 Article en page(s) : pp 53 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] appariement de lignes
[Termes IGN] coplanarité
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtre de Kalman
[Termes IGN] image aérienne
[Termes IGN] itération
[Termes IGN] orientation externeRésumé : (Auteur) This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy. Numéro de notice : A2012-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.52638/rfpt.2012.72 Date de publication en ligne : 21/04/2014 En ligne : https://doi.org/10.52638/rfpt.2012.72 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31870
in Revue Française de Photogrammétrie et de Télédétection > n° 198 - 199 (Septembre 2012) . - pp 53 - 61[article]A framework for integrating multi-accuracy spatial data in geographical applications / Alberto Belussi in Geoinformatica, vol 16 n° 3 (July 2012)
[article]
Titre : A framework for integrating multi-accuracy spatial data in geographical applications Type de document : Article/Communication Auteurs : Alberto Belussi, Auteur ; Sara Migliorini, Auteur Année de publication : 2012 Article en page(s) : pp 523 - 561 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données multisources
[Termes IGN] filtre de Kalman
[Termes IGN] infrastructure nationale des données localisées
[Termes IGN] intégration de données
[Termes IGN] qualité des donnéesRésumé : (Auteur) In recent years the integration of spatial data coming from different sources has become a crucial issue for many geographical applications, especially in the process of building and maintaining a Spatial Data Infrastructure (SDI). In such context new methodologies are necessary in order to acquire and update spatial datasets by collecting new measurements from different sources. The traditional approach implemented in GIS systems for updating spatial data does not usually consider the accuracy of these data, but just replaces the old geometries with the new ones. The application of such approach in the case of an SDI, where continuous and incremental updates occur, will lead very soon to an inconsistent spatial dataset with respect to spatial relations and relative distances among objects. This paper addresses such problem and proposes a framework for representing multi-accuracy spatial databases, based on a statistical representation of the objects geometry, together with a method for the incremental and consistent update of the objects, that applies a customized version of the Kalman filter. Moreover, the framework considers also the spatial relations among objects, since they represent a particular kind of observation that could be derived from geometries or be observed independently in the real world. Spatial relations among objects need also to be compared in spatial data integration and we show that they are necessary in order to obtain a correct result in merging objects geometries. Numéro de notice : A2012-109 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-011-0140-9 Date de publication en ligne : 20/10/2011 En ligne : https://doi.org/10.1007/s10707-011-0140-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31557
in Geoinformatica > vol 16 n° 3 (July 2012) . - pp 523 - 561[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2012031 RAB Revue Centre de documentation En réserve L003 Disponible Evaluation of bayesian despeckling and texture extraction methods based on Gauss–Markov and auto-binomial gibbs random fields: Application to TerraSAR-X data / D. Espinoza Molina in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 2 (May 2012)PermalinkFiltering and segmentation of polarimetric SAR data based on binary partition trees / A. Alonso-Gonzalez in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkA nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage / S. Parrilli in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkCorrection du flou de mouvement sur les images prises de nuit par le STEREOPOLIS / Vincent Daval (2012)PermalinkEntwicklung eines Kalman-Filters zur Bestimmung kurzzeitiger Variationen des Erdschwerefeldes aus daten der Satellitenmission GRACE / E. Kurtenbach (2012)PermalinkFlexible dataset combination and modelling by domain decomposition approaches / Isabelle Panet (2012)PermalinkPermalinkRéduction du chatoiement et apport des données ASAR Envisat et MNE SRTM à la cartographie hydrostructurale du bassin côtier de l'Agnéby (Sud-Est de la côte d'Ivoire) / T. Assoma in Photo interprétation, European journal of applied remote sensing, vol 47 n° 4 (décembre 2011)PermalinkFilling in the gaps: Improving navigation continuity using parallel cascade identification / U. Iqbal in GPS world, vol 22 n° 10 (October 2011)PermalinkAlternative method for angular rate determination within the GOCE gradiometer processing / C. Stummer in Journal of geodesy, vol 85 n° 9 (September 2011)Permalink