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Multiple cues-based active contours for target contour tracking under sophisticated background / Peng Lv in The Visual Computer, vol 33 n°9 (September 2017)
[article]
Titre : Multiple cues-based active contours for target contour tracking under sophisticated background Type de document : Article/Communication Auteurs : Peng Lv, Auteur ; Qingjie Zhao, Auteur ; Yanming Chen, Auteur ; Liujun Zhao, Auteur Année de publication : 2017 Article en page(s) : pp 1103 - 1119 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] couleur (variable spectrale)
[Termes IGN] détection de contours
[Termes IGN] séquence d'images
[Termes IGN] texture d'image
[Termes IGN] traçage
[Termes IGN] vidéo numériqueRésumé : (auteur) In this paper, we propose a novel target contour tracking method under sophisticated background using the multiple cues-based active contour model. To locate the target position, a contour-based mean-shift tracker is designed which combines both color and texture information. To reduce the adverse impact of sophisticated background and also accelerate the curve motion, we propose a two-layer-based target appearance model that combines both discriminative pre-learned-based global layer and voting-based local layer. The proposed appearance model is able to extract rough target region from the complex background, which provides important target region information for our active contour model. We subsequently introduce a dynamical shape model to provide prior target shape information for more stable segmentation. To obtain accurate target boundaries, we design a new multiple cues-based active contour model which integrates with target edge, discriminative region, and shape information. The experimental results on 30 video sequences demonstrate that the proposed method outperforms other competitive contour tracking methods under various tracking environment. Numéro de notice : A2017-406 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-016-1268-2 En ligne : https://doi.org/10.1007/s00371-016-1268-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86286
in The Visual Computer > vol 33 n°9 (September 2017) . - pp 1103 - 1119[article]Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms / Lien T.H. Pham in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)
[article]
Titre : Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms Type de document : Article/Communication Auteurs : Lien T.H. Pham, Auteur Année de publication : 2017 Article en page(s) : pp 86 - 97 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] analyse spectrale
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse forestière
[Termes IGN] carte thématique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] image SPOT 4
[Termes IGN] image SPOT 5
[Termes IGN] mangrove
[Termes IGN] surveillance de la végétation
[Termes IGN] teneur en carbone
[Termes IGN] texture d'image
[Termes IGN] Viet NamRésumé : (Auteur) Mangrove forests are well-known for their provision of ecosystem services and capacity to reduce carbon dioxide concentrations in the atmosphere. Mapping and quantifying mangrove biomass is useful for the effective management of these forests and maximizing their ecosystem service performance. The objectives of this research were to model, map, and analyse the biomass change between 2000 and 2011 of mangrove forests in the Cangio region in Vietnam. SPOT 4 and 5 images were used in conjunction with object-based image analysis and machine learning algorithms. The study area included natural and planted mangroves of diverse species. After image preparation, three different mangrove associations were identified using two levels of image segmentation followed by a Support Vector Machine classifier and a range of spectral, texture and GIS information for classification. The overall classification accuracy for the 2000 and 2011 images were 77.1% and 82.9%, respectively. Random Forest regression algorithms were then used for modelling and mapping biomass. The model that integrated spectral, vegetation association type, texture, and vegetation indices obtained the highest accuracy (R2adj = 0.73). Among the different variables, vegetation association type was the most important variable identified by the Random Forest model. Based on the biomass maps generated from the Random Forest, total biomass in the Cangio mangrove forest increased by 820,136 tons over this period, although this change varied between the three different mangrove associations. Numéro de notice : A2017-332 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.03.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.03.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85485
in ISPRS Journal of photogrammetry and remote sensing > vol 128 (June 2017) . - pp 86 - 97[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017063 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017062 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Cartographic continuum rendering based on color and texture interpolation to enhance photo-realism perception / Charlotte Hoarau in ISPRS Journal of photogrammetry and remote sensing, vol 127 (May 2017)
[article]
Titre : Cartographic continuum rendering based on color and texture interpolation to enhance photo-realism perception Type de document : Article/Communication Auteurs : Charlotte Hoarau , Auteur ; Sidonie Christophe , Auteur Année de publication : 2017 Projets : Mapstyle / Christophe, Sidonie Article en page(s) : pp 27 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] chromatopsie
[Termes IGN] continuité cartographique
[Termes IGN] couche thématique
[Termes IGN] couleur (rédaction cartographique)
[Termes IGN] données maillées
[Termes IGN] données vectorielles
[Termes IGN] interpolation
[Termes IGN] orthoimage
[Termes IGN] rendu réaliste
[Termes IGN] représentation continue
[Termes IGN] texture d'image
[Termes IGN] visualisation de données
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Graphic interfaces of geoportals allow visualizing and overlaying various (visually) heterogeneous geographical data, often by image blending: vector data, maps, aerial imagery, Digital Terrain Model, etc. Map design and geo-visualization may benefit from methods and tools to hybrid, i.e. visually integrate, heterogeneous geographical data and cartographic representations. In this paper, we aim at designing continuous hybrid visualizations between ortho-imagery and symbolized vector data, in order to control a particular visual property, i.e. the photo-realism perception. The natural appearance (colors, textures) and various texture effects are used to drive the control the photo-realism level of the visualization: color and texture interpolation blocks have been developed. We present a global design method that allows to manipulate the behavior of those interpolation blocks on each type of geographical layer, in various ways, in order to provide various cartographic continua. Numéro de notice : A2017-187 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.09.012 Date de publication en ligne : 20/10/2016 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.09.012 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84772
in ISPRS Journal of photogrammetry and remote sensing > vol 127 (May 2017) . - pp 27 - 38[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017053 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017052 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Assessment of textural differentiations in forest resources in Romania using fractal analysis / Ion Andronache in Forests, vol 8 n° 3 (March 2017)
[article]
Titre : Assessment of textural differentiations in forest resources in Romania using fractal analysis Type de document : Article/Communication Auteurs : Ion Andronache, Auteur ; Rasmus Fensholt, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse fractale
[Termes IGN] déboisement
[Termes IGN] image Landsat-ETM+
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] ressources forestières
[Termes IGN] Roumanie
[Termes IGN] texture d'image
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Deforestation and forest degradation have several negative effects on the environment including a loss of species habitats, disturbance of the water cycle and reduced ability to retain CO2, with consequences for global warming. We investigated the evolution of forest resources from development regions in Romania affected by both deforestation and reforestation using a non-Euclidean method based on fractal analysis. We calculated four fractal dimensions of forest areas: the fractal box-counting dimension of the forest areas, the fractal box-counting dimension of the dilated forest areas, the fractal dilation dimension and the box-counting dimension of the border of the dilated forest areas. Fractal analysis revealed morpho-structural and textural differentiations of forested, deforested and reforested areas in development regions with dominant mountain relief and high hills (more forested and compact organization) in comparison to the development regions dominated by plains or low hills (less forested, more fragmented with small and isolated clusters). Our analysis used the fractal analysis that has the advantage of analyzing the entire image, rather than studying local information, thereby enabling quantification of the uniformity, fragmentation, heterogeneity and homogeneity of forests. Numéro de notice : A2017-644 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f8030054 En ligne : http://doi.org/10.3390/f8030054 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86996
in Forests > vol 8 n° 3 (March 2017)[article]New point matching algorithm using sparse representation of image patch feature for SAR image registration / Jianwei Fan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)
[article]
Titre : New point matching algorithm using sparse representation of image patch feature for SAR image registration Type de document : Article/Communication Auteurs : Jianwei Fan, Auteur ; Yan Wu, Auteur ; Fan Wang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1498 - 1510 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] alignement
[Termes IGN] appariement de points
[Termes IGN] chatoiement
[Termes IGN] erreur de discrétisation
[Termes IGN] image radar moirée
[Termes IGN] reconstruction d'image
[Termes IGN] représentation parcimonieuseRésumé : (Auteur) Image registration is an important preprocessing step in many synthetic aperture radar (SAR) image applications. A key issue in image registration is to reliably establish the correspondences between the feature points extracted from the reference and sensed images. A new point matching algorithm is proposed in this paper to align two SAR images. In the proposed method, by considering image patches as the basic units, a novel local descriptor including the intensity and geometric information is assigned to each feature point, which is more robust to speckle noise. Furthermore, a correspondence establishment scheme is introduced based on the reconstruction errors between feature points calculated by the sparse representation (SR) technique, which is designed for achieving accurate matches. Based on the obtained SR coefficients, a coordinate correction procedure is further proposed for improving the localization accuracy of the obtained correspondences. Both simulated deformed and real SAR images are utilized to evaluate the performance. The experimental results indicate that the proposed method yields a better registration performance in terms of both accuracy and robustness. Numéro de notice : A2017-156 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2626373 En ligne : https://doi.org/10.1109/TGRS.2016.2626373 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84692
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 3 (March 2017) . - pp 1498 - 1510[article]Urban slum detection using texture and spatial metrics derived from satellite imagery / Divyani Kohli in Journal of spatial science, vol 61 n° 2 (December 2016)PermalinkDistributed texture-based land cover classification algorithm using hidden Markov model for multispectral data / S. Jenicka in Survey review, vol 48 n° 351 (October 2016)PermalinkHabitat change on Horn Island, Mississippi, 1940-2010, determined from textural features in panchromatic vertical aerial imagery / Guy W. Jeter Jr in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)PermalinkA novel computer-aided tree species identification method based on burst wind segmentation of 3D bark textures / Alice Ahlem Othmani in Machine Vision and Applications, vol 27 n° 5 (July 2016)PermalinkSupervised classification of very high resolution optical images using wavelet-based textural features / Olivier Regniers in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkDeep filter banks for texture recognition, description, and segmentation / Mircea Cimpoi in International journal of computer vision, vol 118 n° 1 (May 2016)PermalinkApport de la télédétection radar satellitaire pour la cartographie de la forêt des Landes / Yousra Hamrouni (2016)PermalinkMultifractal analysis for multivariate data with application to remote sensing / Sébastien Combrexelle (2016)PermalinkPointwise approach for texture analysis and characterization from very high resolution remote sensing images / Minh-Tan Pham (2016)PermalinkMapping slope movements in Alpine environments using TerraSAR-X interferometric methods / Chloé Barboux in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)Permalink