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statistique mathématique
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biométrie,
échantillonnage (statistique), probabilité, statistique. >>Terme(s) spécifique(s) : analyse de régression, analyse de variance, analyse des données, analyse multivariée, analyse séquentielle, calcul d'erreur, carré latin, corrélation (statistique), efficacité asymptotique (statistique), fonction pseudo-aléatoire, loi des grands nombres, modèle linéaire (statistique), modèle non linéaire (statistique), moindre carré, physique statistique, plan d'expérience, rang et sélection (statistique), rupture (statistique), SAS (logiciel), série chronologique, statistique non paramétrique, statistique robuste, tableau de contingence, test d'hypothèses (statistique), statistique stellaire. Equiv. LCSH : Mathematical statistics. Domaine(s) : 510. |
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Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data - part 1: theory / Y.V. Shkvarko in IEEE Transactions on geoscience and remote sensing, vol 42 n° 5 (May 2004)
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Titre : Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data - part 1: theory Type de document : Article/Communication Auteurs : Y.V. Shkvarko, Auteur Année de publication : 2004 Article en page(s) : pp 923 - 931 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] accentuation d'image
[Termes IGN] estimation bayesienne
[Termes IGN] fusion d'imagesRésumé : (Auteur) The problem of estimating, from one sampled realization of the remotely sensed data signal, the power spatial spectrum pattern (SSP) of the wave field scattered from the probing surface is treated as it is required for enhanced radar imaging of the remotely sensed scenes. Specifically, we propose to unify the Bayesian estimation strategy with the maximum-entropy (ME) information-theoretic principle for incorporating the prior knowledge through developing the fused Bayesian-regularization (FBR) technique for SSP estimation. The first aspect of the proposed approach concerns the ME-based incorporating the a priori information about the geometrical properties of an image to tailor the metrics structure in the solution space to the problem at hand. The second aspect alleviates the problem ill-poseness associated with preserving the boundary values, calibration, and spectral a priori fixed model properties of an image through the regularizing projection constraints imposed on the solution. When applied to SSP estimation without incorporating the metrics and regularization considerations, the procedure leads to the previously derived maximum-likelihood method. When such considerations are incorporated, the optimal FBR technique leads to a new nonlinear imaging algorithm that implies adaptive formation of the second-order sufficient statistics of the data, their smoothing, and projection applying the composite regularizing window operator. We provide analytical techniques to find these statistics and windows, and the optimal FBR estimator itself. Numerical recipes, performance issues, and simulation examples are treated in a companion paper. Numéro de notice : A2004-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.823281 En ligne : https://doi.org/10.1109/TGRS.2003.823281 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26720
in IEEE Transactions on geoscience and remote sensing > vol 42 n° 5 (May 2004) . - pp 923 - 931[article] Voir aussiRéservation
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Code-barres Cote Support Localisation Section Disponibilité 065-04051 RAB Revue Centre de documentation En réserve L003 Disponible Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data - part 2: implementation and performance issues / Y.V. Shkvarko in IEEE Transactions on geoscience and remote sensing, vol 42 n° 5 (May 2004)
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Titre : Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data - part 2: implementation and performance issues Type de document : Article/Communication Auteurs : Y.V. Shkvarko, Auteur Année de publication : 2004 Article en page(s) : pp 932 - 940 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] entropie
[Termes IGN] équation non linéaire
[Termes IGN] estimation bayesienne
[Termes IGN] image ERS-SAR
[Termes IGN] implémentation (informatique)
[Termes IGN] inversion
[Termes IGN] méthode robusteRésumé : (Auteur) The fused Bayesian-regularization (FBR) method from a companion paper provides a rigorous theoretical formalism for optimal estimation of the power spatial spectrum pattern (SSP) of the wave field scattered from the probing surface as it is required for enhanced radar imaging of the remotely sensed scenes. Being nonlinear and solution-dependent, the optimal FBR method requires extremely complex nonlinear solution-dependent operator inversions and, therefore, cannot be recommended as a numerically realizable estimator of the SSP. Here, we design a family of robust easy-to-implement FBR algorithms, provide the relevant computational recipes, and discuss their performances. We comment on the practical aspects of the robustified FBR estimators, such as numerical implementation and improvement in the output SNR. The advantage in using the proposed robust FBR method is demonstrated through simulations of enhancing the SAR images formed using the conventional matched filtering of the trajectory signal. Numéro de notice : A2004-194 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.823279 En ligne : https://doi.org/10.1109/TGRS.2003.823279 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26721
in IEEE Transactions on geoscience and remote sensing > vol 42 n° 5 (May 2004) . - pp 932 - 940[article] Voir aussiRéservation
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Code-barres Cote Support Localisation Section Disponibilité 065-04051 RAB Revue Centre de documentation En réserve L003 Disponible Land cover characterization of temperate east Asia using multi-temporal vegetation sensor data / S.H. Boles in Remote sensing of environment, vol 90 n° 4 (30/04/2004)
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Titre : Land cover characterization of temperate east Asia using multi-temporal vegetation sensor data Type de document : Article/Communication Auteurs : S.H. Boles, Auteur ; X. Xiao-Ping, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 477 - 489 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] Asie orientale
[Termes IGN] base de données d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] Enhanced vegetation index
[Termes IGN] image Aqua-MODIS
[Termes IGN] image multitemporelle
[Termes IGN] image SPOT-Végétation
[Termes IGN] image Terra-MODIS
[Termes IGN] occupation du sol
[Termes IGN] photo-identification
[Termes IGN] zone tempéréeRésumé : (Auteur) Temperate East Asia (TEA) is characterized by diverse land cover types, including forest and agricultural lands, one of the world's largest temperate grasslands, and extensive desert and barren landscapes. In this paper, we explored the potential of SPOT-4 VEGETATION (VGT) data for the classification of land cover types in TEA. An unsupervised classification was performed using multi-temporal (March November 2000) VGT-derived spectral indices (Land Surface Water Index [LSWI] and Enhanced Vegetation Index [EVI]) to generate a land cover map of TEA (called VGT-TEA). Land cover classes from VGT-TEA were aggregated to broad, general class types, and then compared and validated with classifications derived from fine-resolution (Landsat) data. VGT-TEA produced reasonable results when compared to the Landsat products. Analysis of the seasonal dynamics of LSWI and EVI allows for the identification of distinct growth patterns between different vegetation types. We suggest that LSWI seasonal curves can be used to define the growing season for temperate deciduous vegetation, including grassland types. Seasonal curves of EVI tend to have a slightly greater dynamic range than LSWI during the peak growing season and can be useful in discriminating between vegetation types. By using these two complementary spectral indices, VGT data can be used to produce timely and detailed land cover and phenology maps with limited ancillary data needed. Numéro de notice : A2004-191 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.01.016 En ligne : https://doi.org/10.1016/j.rse.2004.01.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26718
in Remote sensing of environment > vol 90 n° 4 (30/04/2004) . - pp 477 - 489[article]A sea surface fractal model for ocean remote sensing / F. Berizzi in International Journal of Remote Sensing IJRS, vol 25 n° 7 (April 2004)
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Titre : A sea surface fractal model for ocean remote sensing Type de document : Article/Communication Auteurs : F. Berizzi, Auteur ; E. Dalle Mese, Auteur ; M. Martorella, Auteur Année de publication : 2004 Article en page(s) : pp 1265 - 1270 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse fractale
[Termes IGN] capteur actif
[Termes IGN] flux
[Termes IGN] statistique mathématiqueRésumé : (Auteur) In this letter, we propose and validate a sea surface fractal model suitably tailored for the application of ocean remote sensing by means of active sensors. The model includes both statistical and fractal properties of the surfaces and also accounts for the linear behaviour of sea waves' generation and propagation. Numéro de notice : A2004-089 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001592157 En ligne : https://doi.org/10.1080/01431160310001592157 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26616
in International Journal of Remote Sensing IJRS > vol 25 n° 7 (April 2004) . - pp 1265 - 1270[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04071 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Classification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis / R. Lawrence in Remote sensing of environment, vol 90 n° 3 (15/04/2004)
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Titre : Classification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis Type de document : Article/Communication Auteurs : R. Lawrence, Auteur ; A. Bunn, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 331 - 336 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification
[Termes IGN] décomposition d'image
[Termes IGN] image hyperspectrale
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] image PROBE
[Termes IGN] précision de la classification
[Termes IGN] sylvicultureRésumé : (Auteur) Classification tree analysis (CTA) provides an effective suite of algorithms for classifying remotely sensed data, but it has the limitations of (1) not searching for optimal tree structures and (2) being adversely affected by outliers, inaccurate training data, and unbalanced data sets. Stochastic gradient boosting (SGB) is a refinement of standard CTA that attempts to minimize these limitations by (1) using classification errors to iteratively refine the trees using a random sample of the training data and (2) combining the multiple trees iteratively developed to classify the data. We compared traditional CTA results to SGB for three remote sensing based data sets, an IKONOS image from the Sierra Nevada Mountains of California, a Probe-1 hyperspectral image from the Virginia City mining district of Montana, and a series of Landsat ETM+ images from the Greater Yellowstone Ecosystem (GYE). SGB improved the overall accuracy of the IKONOS classification from 84% to 95% and the Probe-1 classification from 83% to 93%. The worst performing classes using CTA exhibited the largest increases in class accuracy using SGB. A slight decrease in overall classification accuracy resulted from the SGB analysis of the Landsat data. Numéro de notice : A2004-200 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.01.007 En ligne : https://doi.org/10.1016/j.rse.2004.01.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26727
in Remote sensing of environment > vol 90 n° 3 (15/04/2004) . - pp 331 - 336[article]Classifying land development in high-resolution panchromatic satellite images using straight-line statistics / C. Unsalan in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)
PermalinkValidation and calibration of Canada-wide coarse-resolution satellite burned-area maps / R.H. Fraser in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 4 (April 2004)
PermalinkMapping residential density patterns using multi- temporal Landsat data and decision-tree classifier / S. Mccauley in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)
PermalinkSmoothing vegetation spectra with wavelets / K.S. Schmidt in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)
PermalinkTree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI / J. Krishnaswamy in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)
PermalinkHyperion, Ikonos, ALI, and ETM+ sensors in the study of African rainforests / Prasad S. Thenkabail in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
PermalinkIntegrating imaging spectroscopy and neural networks to map grass quality in the Kruger National Park, South Africa / Onisimo Mutanga in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
PermalinkAccuracy analysis of remote sensing change detection by rule-based rationality evaluation with post-classification comparison / H. Liu in International Journal of Remote Sensing IJRS, vol 25 n° 5 (March 2004)
PermalinkAccuracy of airborne lidar derived elevation: empirical assessment and error budget / M.E. Hodgson in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 3 (March 2004)
PermalinkAreas of fuzzy geographical entities / Cidália Costa Fonte in International journal of geographical information science IJGIS, vol 18 n° 2 (march 2004)
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