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Texture augmented detection of macrophyte species using decision trees / Cameron Proctor in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)
[article]
Titre : Texture augmented detection of macrophyte species using decision trees Type de document : Article/Communication Auteurs : Cameron Proctor, Auteur ; Yuhong He, Auteur ; Vincent Robinson, Auteur Année de publication : 2013 Article en page(s) : pp 10 - 20 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algue
[Termes IGN] classification par arbre de décision
[Termes IGN] image panchromatique
[Termes IGN] image Quickbird
[Termes IGN] macrophyte
[Termes IGN] précision de la classification
[Termes IGN] rivière
[Termes IGN] séparabilité
[Termes IGN] texture d'imageRésumé : (Auteur) Image classification using multispectral sensors has shown good performance in detecting macrophytes at the species level. However, species level classification often does not utilize the texture information provided by high resolution images. This study investigated whether image texture provides useful vector(s) for the discrimination of monospecific stands of three floating macrophyte species in Quickbird imagery of the South Nation River. Semivariograms indicated that window sizes of 5 x 5 and 13 x 13 pixels were the most appropriate spatial scales for calculation of the grey level co-occurrence matrix and subsequent texture attributes from the multispectral and panchromatic bands. Of the 214 investigated vectors (13 Haralick texture attributes * 15 bands + 9 spectral bands + 10 transformations/indices), feature selection determined which combination of spectral and textural vectors had the greatest class separability based on the Mann–Whitney U-test and Jefferies–Matusita distance. While multispectral red and near infrared (NIR) performed satisfactorily, the addition of panchromatic-dissimilarity slightly improved class separability and the accuracy of a decision tree classifier (Kappa: red/NIR/panchromatic-dissimilarity – 93.2% versus red/NIR – 90.4%). Class separability improved by incorporating a second texture attribute, but resulted in a decrease in classification accuracy. The results suggest that incorporating image texture may be beneficial for separating stands with high spatial heterogeneity. However, the benefits may be limited and must be weighed against the increased complexity of the classifier. Numéro de notice : A2013-295 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.022 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.02.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32433
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 10 - 20[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible A sparse image fusion algorithm with application to pan-sharpening / Xiao Xiang Zhu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)
[article]
Titre : A sparse image fusion algorithm with application to pan-sharpening Type de document : Article/Communication Auteurs : Xiao Xiang Zhu, Auteur ; Richard Bamler, Auteur Année de publication : 2013 Article en page(s) : pp 2827 - 2836 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] compression d'image
[Termes IGN] fusion d'images
[Termes IGN] image à haute résolution
[Termes IGN] image Geoeye
[Termes IGN] image Ikonos
[Termes IGN] image panchromatique
[Termes IGN] image Quickbird
[Termes IGN] méthode robuste
[Termes IGN] pansharpening (fusion d'images)Résumé : (Auteur) Data provided by most optical Earth observation satellites such as IKONOS, QuickBird, and GeoEye are composed of a panchromatic channel of high spatial resolution (HR) and several multispectral channels at a lower spatial resolution (LR). The fusion of an HR panchromatic and the corresponding LR spectral channels is called “pan-sharpening.” It aims at obtaining an HR multispectral image. In this paper, we propose a new pan-sharpening method named Sparse Fusion of Images (SparseFI, pronounced as “sparsify”). SparseFI is based on the compressive sensing theory and explores the sparse representation of HR/LR multispectral image patches in the dictionary pairs cotrained from the panchromatic image and its downsampled LR version. Compared with conventional methods, it “learns” from, i.e., adapts itself to, the data and has generally better performance than existing methods. Due to the fact that the SparseFI method does not assume any spectral composition model of the panchromatic image and due to the super-resolution capability and robustness of sparse signal reconstruction algorithms, it gives higher spatial resolution and, in most cases, less spectral distortion compared with the conventional methods. Numéro de notice : A2013-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2213604 En ligne : https://doi.org/10.1109/TGRS.2012.2213604 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32397
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 5 Tome 1 (May 2013) . - pp 2827 - 2836[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013051A RAB Revue Centre de documentation En réserve L003 Disponible Boundary-constrained multi-scale segmentation method for remote sensing images / Xueliang Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)
[article]
Titre : Boundary-constrained multi-scale segmentation method for remote sensing images Type de document : Article/Communication Auteurs : Xueliang Zhang, Auteur ; Pengfeng Xiao, Auteur ; Xiaoqun Song, Auteur Année de publication : 2013 Article en page(s) : pp 15 - 25 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] contrainte géométrique
[Termes IGN] données multiéchelles
[Termes IGN] image Quickbird
[Termes IGN] image Worldview
[Termes IGN] segmentation d'imageRésumé : (Auteur) Image segmentation is the key step of Object-Based Image Analysis (OBIA) in remote sensing. This paper proposes a Boundary-Constrained Multi-Scale Segmentation (BCMS) method. Firstly, adjacent pixels are aggregated to generate initial segmentation according to the local best region growing strategy. Then, the Region Adjacency Graph (RAG) is built based on initial segmentation. Finally, the local mutual best region merging strategy is applied on RAG to produce multi-scale segmentation results. During the region merging process, a Step-Wise Scale Parameter (SWSP) strategy is proposed to produce boundary-constrained multi-scale segmentation results. Moreover, in order to improve the accuracy of object boundaries, the property of edge strength is introduced as a merging criterion. A set of high spatial resolution remote sensing images is used in the experiment, e.g., QuickBird, WorldView, and aerial image, to evaluate the effectiveness of the proposed method. The segmentation results of BCMS are compared with those of the commercial image analysis software eCognition. The experiment shows that BCMS can produce nested multi-scale segmentations with accurate and smooth boundaries, which proves the robustness of the proposed method. Numéro de notice : A2013-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.01.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.01.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32315
in ISPRS Journal of photogrammetry and remote sensing > vol 78 (April 2013) . - pp 15 - 25[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013041 RAB Revue Centre de documentation En réserve L003 Disponible Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery / Ali Ozgun Ok in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 2 (March 2013)
[article]
Titre : Automated detection of arbitrarily shaped buildings in complex environments from monocular VHR optical satellite imagery Type de document : Article/Communication Auteurs : Ali Ozgun Ok, Auteur ; Caglar Seranas, Auteur ; Baris Yuksel, Auteur Année de publication : 2013 Article en page(s) : pp 1701 - 1717 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection de régions
[Termes IGN] détection du bâti
[Termes IGN] image à très haute résolution
[Termes IGN] image Geoeye
[Termes IGN] image Quickbird
[Termes IGN] information complexe
[Termes IGN] ombre
[Termes IGN] partition des donnéesRésumé : (Auteur) This paper introduces a new approach for the automated detection of buildings from monocular very high resolution (VHR) optical satellite images. First, we investigate the shadow evidence to focus on building regions. To do that, we propose a new fuzzy landscape generation approach to model the directional spatial relationship between buildings and their shadows. Once all landscapes are collected, a pruning process is developed to eliminate the landscapes that may occur due to non-building objects. The final building regions are detected by GrabCut partitioning approach. In this paper, the input requirements of the GrabCut partitioning are automatically extracted from the previously determined shadow and landscape regions, so that the approach gained an efficient fully automated behavior for the detection of buildings. Extensive experiments performed on 20 test sites selected from a set of QuickBird and Geoeye-1 VHR images showed that the proposed approach accurately detects buildings with arbitrary shapes and sizes in complex environments. The tests also revealed that even under challenging environmental and illumination conditions, reasonable building detection performances could be achieved by the proposed approach. Numéro de notice : A2013-135 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2207905 En ligne : https://doi.org/10.1109/TGRS.2012.2207905 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32273
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 3 Tome 2 (March 2013) . - pp 1701 - 1717[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013031B RAB Revue Centre de documentation En réserve L003 Disponible Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region / George P. Petropoulos in Geocarto international, vol 28 n° 1-2 (February - May 2013)
[article]
Titre : Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region Type de document : Article/Communication Auteurs : George P. Petropoulos, Auteur ; Krishna Prasad Vadrevu, Auteur ; Chariton Kalaitzidis, Auteur Année de publication : 2013 Article en page(s) : pp 114 - 129 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification orientée objet
[Termes IGN] classification Spectral angle mapper
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] image Quickbird
[Termes IGN] littoral méditerranéen
[Termes IGN] matrice d'erreur
[Termes IGN] occupation du solRésumé : (Auteur) In this study, we test the potential of two different classification algorithms, namely the spectral angle mapper (SAM) and object-based classifier for mapping the land use/cover characteristics using a Hyperion imagery. We chose a study region that represents a typical Mediterranean setting in terms of landscape structure, composition and heterogeneous land cover classes. Accuracy assessment of the land cover classes was performed based on the error matrix statistics. Validation points were derived from visual interpretation of multispectral high resolution QuickBird-2 satellite imagery. Results from both the classifiers yielded more than 70% classification accuracy. However, the object-based classification clearly outperformed the SAM by 7.91% overall accuracy (OA) and a relatively high kappa coefficient. Similar results were observed in the classification of the individual classes. Our results highlight the potential of hyperspectral remote sensing data as well as object-based classification approach for mapping heterogeneous land use/cover in a typical Mediterranean setting. Numéro de notice : A2013-278 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.668950 Date de publication en ligne : 02/04/2012 En ligne : https://doi.org/10.1080/10106049.2012.668950 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32416
in Geocarto international > vol 28 n° 1-2 (February - May 2013) . - pp 114 - 129[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2013011 RAB Revue Centre de documentation En réserve L003 Disponible PermalinkCartographie des zones humides de montagne par télédétection : Potentialités des images à très haute résolution spatiale / L. Vacquié in Revue internationale de géomatique, vol 22 n° 4 (décembre 2012 – février 2013)PermalinkExtraction du trait instantané de côte à partir d'images optiques satellites haute-résolution et radar / Valerio Baiocchi in Géomatique expert, n° 89 (01/11/2012)PermalinkCombined use of Quickbird and lidar data for mapping a urban environment / N.B. Da Luz in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)PermalinkProposta de uma metodologia econômica para o desenvolvimento de SIG 3D / M.A. Nero in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)PermalinkAutomatic detection and segmentation of orchards using very high resolution imagery / Selim Aksoy in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkSynthesizing urban remote sensing through application, scale, data and case studies / E.A. Wentz in Geocarto international, vol 27 n° 5 (August 2012)PermalinkUse of high-resolution satellite imagery for investigating acid mine drainage from artisanal coal mining in North-Eastern India / B. Blahwar in Geocarto international, vol 27 n° 3 (June 2012)PermalinkExposure estimation from multi-resolution optical satellite imagery for seismic risk assessment / Marc Wieland in ISPRS International journal of geo-information, vol 1 n°1 (March 2012)PermalinkA new pan-sharpening method using multiobjective particle swarm optimization and the shiftable contourlet transform / J. Saeedi in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 3 (May - June 2011)Permalink