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SAR image change detection based on correlation kernel and multistage extreme learning machine / Lu Jia in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
[article]
Titre : SAR image change detection based on correlation kernel and multistage extreme learning machine Type de document : Article/Communication Auteurs : Lu Jia, Auteur ; Ming Li, Auteur ; Peng Zhang, Auteur ; Yan Wu, Auteur Année de publication : 2016 Article en page(s) : pp 5993 - 6006 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] appariement d'images
[Termes IGN] apprentissage automatique
[Termes IGN] détection de changement
[Termes IGN] détection de contours
[Termes IGN] image radar moirée
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] séparateur à vaste margeRésumé : (auteur) Designing a kernel function with good discriminating ability and a highly application-adaptive kernelized classifier is the key of many kernel methods. However, not many kernel functions combining directly the bitemporal images' information are designed specifically for change detection tasks. In addition, extreme learning machine (ELM) has not found wide applications in change detection tasks, even though it is a potential kernel method possessing outstanding approximation and generalization capabilities as well as great classification accuracy and efficiency. Therefore, an approach relying on a difference correlation kernel (DCK) and a multistage ELM (MS-ELM) is proposed in this paper for synthetic aperture radar (SAR) image change detection. First, a DCK function is constructed specifically for change detection by measuring the “distance” between any two pixels. The DCK function depicts the cross-time similarities between couples of bitemporal image patches at any cyclic shifts with a kernel correlation operation and the high-order spatial distances between two differently located pixels with an algebraic subtraction. The DCK function possesses strong noise immunity and good identification of changed areas simultaneously. Second, an MS-ELM classifier is constructed for obtaining the change detection result. In MS-ELM, the hidden nodes and weights between the hidden and output layers are updated stage by stage by improving the kernel functions that compose them. Each stage of the MS-ELM is a standard kernel-ELM, and the DCK function is utilized in the first stage. The regenerative kernel functions incorporate the output spatial-neighborhood information of the previous stage for enhancing remarkably the MS-ELM's discriminating ability and noise resistance. The converged result at the last stage of MS-ELM is the final change detection result. Experiments on real SAR image change detection demonstrate the effectiveness of the DCK function and the MS-ELM algorithm, particularly its good identification of changed areas and strong robustness against noise in SAR images. Numéro de notice : A2016-865 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2578438 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2578438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82901
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 10 (October 2016) . - pp 5993 - 6006[article]Automatic delineation of built-up area at urban block level from topographic maps / Sebastian Muhs in Computers, Environment and Urban Systems, vol 58 (July 2016)
[article]
Titre : Automatic delineation of built-up area at urban block level from topographic maps Type de document : Article/Communication Auteurs : Sebastian Muhs, Auteur ; Hendrik Herold, Auteur ; Gotthard Meinel, Auteur ; Dirk Burghardt, Auteur ; Odette Kretschmer, Auteur Année de publication : 2016 Article en page(s) : pp 71 - 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image numérique
[Termes IGN] base de données historiques
[Termes IGN] carte topographique
[Termes IGN] détection du bâti
[Termes IGN] extraction semi-automatique
[Termes IGN] îlot urbain
[Termes IGN] vision par ordinateur
[Termes IGN] zone urbaineRésumé : (auteur) To comprehensively study and better understand urban dynamic processes — such as densification, growth and sprawl, or shrinkage — spatio-temporal databases that allow to track changes of geographic objects like buildings and urban blocks are essential. While comprehensive databases exist for contemporary data, they usually lack a historic dimension. The manual constitution of historic geographic data, be it based on historic maps or aerial images, is a time consuming and laborious process, however. Therefore, we present an approach to semi-automatically extract this data from binary topographic maps with regard to built-up areas at urban block level. The suitability of topographic maps for historic urban analysis has been proven in previous research. To overcome the challenges that are inherent in scanned topographic maps in regard to digital image interpretation we designed a modular process. Among others, these challenges include fused and (multi-)fragmented map objects caused by the overlap of competing content layers in one single binary map. After a preliminary separation of individual map object layers from the map content, the process follows a two-stage top-down approach. At first, the map is organized into street blocks, which after that are re-delineated in regard to built-up area. In doing so, we achieve correctness values ranging from 0.97 to 0.93 for three study sites in Germany. With an increasing number of projects that provide historic topographic maps as georeferenced digital data, our process represents a promising approach to efficiently prepare these historic data for integration into a spatio-temporal database with minimal user intervention. Numéro de notice : A2016-404 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2016.04.001 En ligne : http://dx.doi.org/10.1016/j.compenvurbsys.2016.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81221
in Computers, Environment and Urban Systems > vol 58 (July 2016) . - pp 71 - 84[article]Classifying buildings from point clouds and images / Evangelos Maltezos in GIM international, vol 30 n° 7 (July 2016)
[article]
Titre : Classifying buildings from point clouds and images Type de document : Article/Communication Auteurs : Evangelos Maltezos, Auteur ; Charalabos Ioannnidis, Auteur Année de publication : 2016 Article en page(s) : pp 18 - 21 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] appariement d'images
[Termes IGN] classification dirigée
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] Grèce
[Termes IGN] image optique
[Termes IGN] semis de pointsRésumé : (éditeur) The reconstruction of building outlines provide useful input for land information system. In the city of Kalochory in nethern Greece, a mixed commercial and residential of 33 hectares was selected as a test area to evaluate the classification of buildings. Two data sources were avalaible: airborn Lidar and photographs. These data sources were procesesed to create two separate point clouds.Comparison of the results shows that both data sources can be used for building classification, although more development is needed to improve the robustness of dense image matching. Numéro de notice : A2016-490 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81508
in GIM international > vol 30 n° 7 (July 2016) . - pp 18 - 21[article]Registration-based mapping of aboveground disparities (RMAD) for building detection in off-nadir VHR stereo satellite imagery / Suliman Alaeldin in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)
[article]
Titre : Registration-based mapping of aboveground disparities (RMAD) for building detection in off-nadir VHR stereo satellite imagery Type de document : Article/Communication Auteurs : Suliman Alaeldin, Auteur ; Yun Zhang, Auteur ; Raid Al-Tahir, Auteur Année de publication : 2016 Article en page(s) : pp 535 - 546 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] détection du bâti
[Termes IGN] disparité
[Termes IGN] image à très haute résolution
[Termes IGN] modèle stéréoscopique
[Termes IGN] traitement d'image
[Termes IGN] visée obliqueRésumé : (Auteur) Reliable building delineation in very high resolution (VHR) satellite imagery can be achieved by precise disparity information extracted from stereo pairs. However, off-nadir VHR images over urban areas contain many occlusions due to building leaning that creates gaps in the extracted disparity maps. The typical approach to fill these gaps is by interpolation. However, it inevitably degrades the quality of the disparity map and reduces the accuracy of building detection. Thus, this research proposes a registration-based technique for mapping the disparity of off-terrain objects to avoid the need for disparity interpolation and normalization. The generated disparity by the proposed technique is then used to support building detection in off-nadir VHR satellite images. Experiments in a high-rise building area confirmed that 75 percent of the detected building roofs overlap precisely the reference data, with almost 100 percent correct detection. These accuracies are substantially higher than those achieved by other published research. Numéro de notice : A2016-515 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.7.535 En ligne : http://dx.doi.org/10.14358/PERS.82.7.535 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81586
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 7 (juillet 2016) . - pp 535 - 546[article]Comparison of quality measures for building outline extraction / Markéta Potůčková in Photogrammetric record, vol 31 n° 154 (June - August 2016)
[article]
Titre : Comparison of quality measures for building outline extraction Type de document : Article/Communication Auteurs : Markéta Potůčková, Auteur ; Peter Hofman, Auteur Année de publication : 2016 Article en page(s) : pp 193 - 209 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection automatique
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] estimation de précision
[Termes IGN] lasergrammétrie
[Termes IGN] qualité des donnéesRésumé : (auteur) To date, numerous automatic building detection methods using lidar data have been developed. However, in most cases the parameters used for the evaluation of the results are not specified, accuracy assessment results cannot be readily compared or no result evaluation is performed at all. In this study, accuracy assessment aspects have been analysed in order to find a generally applicable approach for the comparison of building outline extraction methods. An area-based evaluation of accuracy has been selected as the most suitable due to its robustness, predictability and comparability between datasets. This assessment can be further supplemented with both object- and area-based evaluations, procured solely with those buildings that were classified as true positives, in order to interpret the extraction results in more detail. In cases where a reference dataset of superior quality (such as low-altitude aerial imagery) is available, an absolute accuracy evaluation is also relevant. Numéro de notice : A2016-468 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12144 Date de publication en ligne : 17/06/2016 En ligne : https://doi.org/10.1111/phor.12144 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81474
in Photogrammetric record > vol 31 n° 154 (June - August 2016) . - pp 193 - 209[article]Réservation
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