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Optimal segmentation of high spatial resolution images for the classification of buildings using random forests / James Bialas in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 82 (October 2019) . - pp Titre : Optimal segmentation of high spatial resolution images for the classification of buildings using random forests Type de document : Article/Communication Auteurs : James Bialas, Auteur ; Thomas Oommen, Auteur ; Timothy C. Havens, Auteur Année de publication : 2019 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] bâtiment [Termes descripteurs IGN] Christchurch [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] dommage matériel [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] qualité du processus [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] séisme [Termes descripteurs IGN] zone urbaine Résumé : (auteur) In the application of machine learning to geographic object based image analysis, several parameters influence overall classifier performance. One of the first parameters is segmentation size—for example, how many pixels should be grouped together to form an image object. Often, trial and error methods are used to obtain segmentation parameters that best delineate the borders of real world objects. Several attempts at automated methods have produced promising results, but manual intervention is still necessary. Meanwhile, numerous measures of segmentation quality have been defined, but their relationship to classifier performance is not then directly shown. For example, as measures of segmentation quality improve, do classification results improve as well? Our work considers the problem of building classification in high resolution aerial imagery of urban areas. Based on user defined training polygons generated with or without a reference segmentation, we have found several measures of segmentation quality and feature performance that can help users narrow the range of appropriate segmentations. Furthermore, our work finds that given this range, performance of machine learning algorithms remains relatively constant for any given segmentation as long as features used for classification are chosen correctly. We find that the range of scale parameters capable of producing an accurate classification is much broader than typically assumed and trial and error methods for finding this parameter may be an acceptable approach. Numéro de notice : A2019-472 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2019.06.005 date de publication en ligne : 08/06/2019 En ligne : https://doi.org/https://doi.org/10.1016/j.jag.2019.06.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93632 [article]

Review of mobile laser scanning target‐free registration methods for urban areas using improved error metrics / Hoang Long Nguyen in Photogrammetric record, vol 34 n° 167 (September 2019)  

Public [article]  inPhotogrammetric record > vol 34 n° 167 (September 2019) . - pp 282 – 303 Titre : Review of mobile laser scanning target‐free registration methods for urban areas using improved error metrics Type de document : Article/Communication Auteurs : Hoang Long Nguyen, Auteur ; David Belton, Auteur ; Petra Helmholz, Auteur Année de publication : 2019 Article en page(s) : pp 282 – 303 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] algorithme ICP [Termes descripteurs IGN] appariement de points [Termes descripteurs IGN] erreur de mesure [Termes descripteurs IGN] qualité du processus [Termes descripteurs IGN] traitement de nuage de points [Termes descripteurs IGN] zone urbaine Mots-clés libres : The aim of the registration process is to obtain the transformation parameters to transform captured point clouds to their correct positions. Résumé : (auteur) Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper firstly reviews existing target‐free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account the residuals of check planes as well as their orientation. Experiments using real datasets in combination with reference data were performed to evaluate the suitability of these metrics. The proposed error metric proved to be more suitable for evaluating the quality of point cloud registration than state‐of‐the‐art equivalents. The results also indicate that least squares plane fitting is the best technique for MLS point cloud registration. Numéro de notice : A2019-498 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12293 date de publication en ligne : 10/10/2019 En ligne : https://doi.org/10.1111/phor.12293 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93760 [article]

The Parallel SBAS approach for Sentinel-1 interferometric wide swath deformation time-series generation: algorithm description and products quality assessment / Michele Manunta in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6259 - 6281 Titre : The Parallel SBAS approach for Sentinel-1 interferometric wide swath deformation time-series generation: algorithm description and products quality assessment Type de document : Article/Communication Auteurs : Michele Manunta, Auteur ; Claudio De Luca, Auteur ; Ivana Zinno, Auteur ; Francesco Casu, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 6259 - 6281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] interferométrie différentielle [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] Italie [Termes descripteurs IGN] qualité du processus [Termes descripteurs IGN] série temporelle Résumé : (auteur) We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015–April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h. The presented results demonstrate the capability of the implemented P-SBAS approach to efficiently and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale. Numéro de notice : A2019-624 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2904912 date de publication en ligne : 24/05/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2904912 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93374 [article]

Quality assessment in point feature generalization with pattern preserved / Wenhao Yu in Transactions in GIS, vol 22 n° 3 (June 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 3 (June 2018) . - pp 872 - 888 Titre : Quality assessment in point feature generalization with pattern preserved Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur Année de publication : 2018 Article en page(s) : pp 872 - 888 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] objet géographique ponctuel [Termes descripteurs IGN] qualité du processus [Vedettes matières IGN] Généralisation Résumé : (Auteur) Geographical features often show certain spatial patterns on a map in terms of the arrangement of point symbols. These patterns are essentially related to the underlying geographical processes and landscapes. Thus, when deriving small‐scale maps from a large‐scale map, one of the most important constraints that cartographers or systems should follow is to retain the basic patterns of point objects on the target map. However, no research in the literature currently evaluates the quality of point feature generalization in terms of spatial pattern. This study proposes an approach to quantitatively measure the pattern change after generalization. The basic idea of the approach is to extend advanced image analysis techniques (e.g., texture recognition) to measure the patterns of point objects in a map space. Specifically, there are two main steps: firstly, the original space is converted into the raster space by utilizing a regularly spaced grid (i.e., a grayscale image) with cell attributes representing the local intensity level of point features; secondly, the texture analysis operation is performed on the grid to obtain the feature descriptors of the point pattern. The experimental results demonstrate that the proposed approach is effective in comparing the point patterns before and after generalization. Numéro de notice : A2018-581 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12339 date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1111/tgis.12339 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92329 [article]

Pan-sharpening quality investigation of PLÉIADES-1A images / Mustafa Ozendi in Geocarto international, vol 31 n° 7 - 8 (July - August 2016)  

Public [article]  inGeocarto international > vol 31 n° 7 - 8 (July - August 2016) . - pp 881 - 890 Titre : Pan-sharpening quality investigation of PLÉIADES-1A images Type de document : Article/Communication Auteurs : Mustafa Ozendi, Auteur ; Hyseyin Topan, Auteur ; Murat Oruc, Auteur ; Ali Cam, Auteur Année de publication : 2016 Article en page(s) : pp 881 - 890 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] affinage d'image [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] évaluation des données [Termes descripteurs IGN] image Pléiades-HR [Termes descripteurs IGN] pansharpening (fusion d'images) [Termes descripteurs IGN] qualité du processus [Termes descripteurs IGN] transformation de Brovey [Termes descripteurs IGN] transformation intensité-teinte-saturation Résumé : (Auteur) Optical remote sensing satellites obtain MS and Pan images simultaneously over the same coverage area. Remote sensing and image processing communities are working on different pan-sharpening methods capable of taking advantage of MS and Pan images. Each remote sensing system has its own advantages and disadvantages, leading to the question ‘Which pan-sharpening method should be used for which type of imagery?’ The aim of this research is to investigate the pan-sharpening performance of PLÉIADES-1A images. For this purpose, pan-sharpened images were generated using PCA, IHS and Brovey Transform which are the most popular pan-sharpening methods. Then, the pan-sharpened images were evaluated quantitatively using Correlation Coefficient, Root Mean Square Error, Relative Average Spectral Error, Spectral Angle Mapper and Erreur Relative Globale Adimensionnelle de Synthése. In addition, pan-sharpened images were evaluated qualitatively by taking object availability and completeness into consideration. Numéro de notice : A2016-459 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094520 date de publication en ligne : 20/10/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81383 [article]

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