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No-reference image quality assessment for image auto-denoising / Xiangfei Kong in International journal of computer vision, vol 126 n° 5 (May 2018)
[article]
Titre : No-reference image quality assessment for image auto-denoising Type de document : Article/Communication Auteurs : Xiangfei Kong, Auteur ; Qingxiong Yang, Auteur Année de publication : 2018 Article en page(s) : pp 537 - 549 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] filtrage du bruit
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] qualité d'imageRésumé : (Auteur) This paper proposes two new non-reference image quality metrics that can be adopted by the state-of-the-art image/video denoising algorithms for auto-denoising. The first metric is proposed based on the assumption that the noise should be independent of the original image. A direct measurement of this dependence is, however, impractical due to the relatively low accuracy of existing denoising method. The proposed metric thus tackles the homogeneous regions and highly-structured regions separately. Nevertheless, this metric is only stable when the noise level is relatively low. Most denoising algorithms reduce noise by (weighted) averaging repeated noisy measurements. As a result, another metric is proposed for high-level noise based on the fact that more noisy measurements will be required when the noise level increases. The number of measurements before converging is thus related to the quality of noisy images. Our patch-matching based metric proposes to iteratively find and add noisy image measurements for averaging until there is no visible difference between two successively averaged images. Both metrics are evaluated on LIVE2 (Sheikh et al. in LIVE image quality assessment database release 2: 2013) and TID2013 (Ponomarenko et al. in Color image database tid2013: Peculiarities and preliminary results: 2005) data sets using standard Spearman and Kendall rank-order correlation coefficients (ROCC), showing that they subjectively outperforms current state-of-the-art no-reference metrics. Quantitative evaluation w.r.t. different level of synthetic noisy images also demonstrates consistently higher performance over state-of-the-art non-reference metrics when used for image denoising. Numéro de notice : A2018-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-017-1054-2 Date de publication en ligne : 17/11/2017 En ligne : https://doi.org/10.1007/s11263-017-1054-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90883
in International journal of computer vision > vol 126 n° 5 (May 2018) . - pp 537 - 549[article]Aggregate keyword nearest neighbor queries on road networks / Pengfei Zhang in Geoinformatica, vol 22 n° 2 (April 2018)
[article]
Titre : Aggregate keyword nearest neighbor queries on road networks Type de document : Article/Communication Auteurs : Pengfei Zhang, Auteur ; Huaizhong Lin, Auteur ; Yunjun Gao, Auteur ; Dongming Lu, Auteur Année de publication : 2018 Article en page(s) : pp 237 - 268 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] langage naturel (informatique)
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] point d'intérêt
[Termes IGN] requête spatiale
[Termes IGN] réseau routier
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Given a group Q of query points and a set P of points of interest (POIs), aggregate nearest neighbor (ANN) queries find a POI p from P that achieves the smallest aggregate distance. Specifically, the aggregate distance is defined over the set of distances between p and all query points in Q$\mathcal {Q}$. Existing studies on ANN query mainly consider the spatial proximity, whereas the textual similarity has received considerable attention recently. In this work, we utilize user-specified query keywords to capture textual similarity. We study the aggregate keyword nearest neighbor (AKNN) queries, finding the POI that has the smallest aggregate distance and covers all query keywords. Nevertheless, existing methods on ANN query are either inapplicable or inefficient when applied to the AKNN query. To answer our query efficiently, we first develop a dual-granularity (DG) indexing schema. It preserves abstracts of the road network by a tree structure, and preserves detailed network information by an extended adjacency list. Then, we propose a minimal first search (MFS) algorithm. It traverses the tree and explores the node with the minimal aggregate distance iteratively. This method suffers from false hits arising from keyword tests. Thus, we propose the collaborative filtering technique, which performs keywords test by multiple keyword bitmaps collectively rather than by only one. Extensive experiments on both real and synthetic datasets demonstrate the superiority of our algorithms and optimizing strategies. Numéro de notice : A2018-364 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-017-0315-0 Date de publication en ligne : 29/12/2017 En ligne : https://doi.org/10.1007/s10707-017-0315-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90726
in Geoinformatica > vol 22 n° 2 (April 2018) . - pp 237 - 268[article]The characteristics of asymmetric pedestrian behavior : A preliminary study using passive smartphone location data / Nick Malleson in Transactions in GIS, vol 22 n° 2 (April 2018)
[article]
Titre : The characteristics of asymmetric pedestrian behavior : A preliminary study using passive smartphone location data Type de document : Article/Communication Auteurs : Nick Malleson, Auteur ; Anthony Vanky, Auteur ; Behrooz Hashemian, Auteur ; Paolo Santi, Auteur ; Santosh K. Verma, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 616 - 634 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] chemin le plus court, algorithme du
[Termes IGN] matrice
[Termes IGN] piéton
[Termes IGN] téléphone intelligent
[Termes IGN] trace numériqueRésumé : (Auteur) Understanding the movements of people is essential for the design and management of urban areas. This article presents a novel approach to understanding the asymmetry in route choice (i.e., the degree to which people choose different walking routes for their outbound and return journeys). The study utilizes a large volume of traces of individual routes, captured using a smartphone application. The routes are aggregated to a regular grid, and matrix statistics are developed to estimate the aggregate degree of route asymmetry for different types of route (shortest, longest, weekday, weekend, etc.). The results suggest that people change their route approximately 15% of the time. Although this varied little when observing trips made at the weekend or on a weekday, people taking journeys that deviated substantially from the shortest possible path were 6 percentage points less likely to change their routes than those taking journeys that were closest to the shortest path (14 and 20% asymmetry, respectively). The absolute length also impacted on the asymmetry of journeys, but not as substantially. This result is important because, for the first time, it reports a correlation between deviation from shortest route and aggregate pedestrian choice. Numéro de notice : A2018-218 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12336 Date de publication en ligne : 06/04/2018 En ligne : https://doi.org/10.1111/tgis.12336 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90010
in Transactions in GIS > vol 22 n° 2 (April 2018) . - pp 616 - 634[article]European Forest Types: toward an automated classification / Francesca Giannetti in Annals of Forest Science, vol 75 n° 1 (March 2018)
[article]
Titre : European Forest Types: toward an automated classification Type de document : Article/Communication Auteurs : Francesca Giannetti, Auteur ; Anna Barbati, Auteur ; Leone Davide Mancini, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de tri
[Termes IGN] base de règles
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification pixellaire
[Termes IGN] Europe (géographie physique)
[Termes IGN] Fagus (genre)
[Termes IGN] milieu naturel
[Termes IGN] système d'information forestier
[Termes IGN] système d'information géographique
[Termes IGN] système expert
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Key message: The outcome of the present study leads to the application of a spatially explicit rule-based expert system (RBES) algorithm aimed at automatically classifying forest areas according to the European Forest Types (EFT) system of nomenclature at pan-European scale level. With the RBES, the EFT system of nomenclature can be now easily implemented for objective, replicable, and automatic classification of field plots for forest inventories or spatial units (pixels or polygons) for thematic mapping.
Context: Forest Types classification systems are aimed at stratifying forest habitats. Since 2006, a common scheme for classifying European forests into 14 categories and 78 types (European Forest Types, EFT) exists.
Aims: This work presents an innovative method and automated classification system that, in an objective and replicable way, can accurately classify a given forest habitat according to the EFT system of nomenclature.
Methods: A rule-based expert system (RBES) was adopted as a transparent approach after comparison with the well-known Random Forest (RF) classification system. The experiment was carried out based on the information acquired in the field in 2010 ICP level I plots in 17 European countries. The accuracy of the automated classification is evaluated by comparison with an independent classification of the ICP plots into EFT carried out during the BioSoil project field survey. Finally, the RBES automated classifier was tested also for a pixel-based classification of a pan-European distribution map of beech-dominated forests.
Results: The RBES successfully classified 94% of the plots, against a 92% obtained with RF. When applied to the mapped domain, the accuracy obtained with the RBES for the beech forest map classification was equal to 95%.
Conclusion: The RBES algorithm successfully automatically classified field plots and map pixels on the basis of the EFT system of nomenclature. The EFT system of nomenclature can be now easily and objectively implemented in operative transnational European forest monitoring programs.Numéro de notice : A2018-318 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-017-0674-6 Date de publication en ligne : 03/01/2018 En ligne : https://doi.org/10.1007/s13595-017-0674-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90450
in Annals of Forest Science > vol 75 n° 1 (March 2018)[article]Harmonic regression of Landsat time series for modeling attributes from national forest inventory data / Barry T. Wilson in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
[article]
Titre : Harmonic regression of Landsat time series for modeling attributes from national forest inventory data Type de document : Article/Communication Auteurs : Barry T. Wilson, Auteur ; Joseph F. Knight, Auteur ; Ronald E. McRoberts, Auteur Année de publication : 2018 Article en page(s) : pp 29 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attribut
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] régression harmonique
[Termes IGN] série temporelleRésumé : (Auteur) Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009–2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10–20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher. Numéro de notice : A2018-077 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89439
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 29 - 46[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding / Florian W. Fichtner in Transactions in GIS, vol 22 n° 1 (February 2018)PermalinkPermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkLocalisation par l'image en milieu urbain : application à la réalité augmentée / Antoine Fond (2018)PermalinkSocial Distance metric: from coordinates to neighborhoods / Vagan Terziyan in International journal of geographical information science IJGIS, vol 31 n° 11-12 (November - December 2017)PermalinkHub Labels on the database for large-scale graphs with the COLD framework / Alexandros Efentakis in Geoinformatica, vol 21 n° 4 (October - December 2017)PermalinkSnapshot and continuous points-based trajectory search / Shuyao Qi in Geoinformatica, vol 21 n° 4 (October - December 2017)PermalinkUncertain Voronoi cell computation based on space decomposition / Klaus Arthur Schmid in Geoinformatica, vol 21 n° 4 (October - December 2017)PermalinkCrowdsourcing a cyclist perspective on suggested recreational paths in real-world networks / Kevin Baker in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)PermalinkRéduction de l'erreur systématique de mesure géométrique par enrichissement altimétrique des données géographiques / Jean-François Girres in Cartes & Géomatique, n° 233 (septembre - novembre 2017)Permalink