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Deep filter banks for texture recognition, description, and segmentation / Mircea Cimpoi in International journal of computer vision, vol 118 n° 1 (May 2016)
[article]
Titre : Deep filter banks for texture recognition, description, and segmentation Type de document : Article/Communication Auteurs : Mircea Cimpoi, Auteur ; Subhransu Maji, Auteur ; Iasonas Kokkinos, Auteur ; Andrea Vedaldi, Auteur Année de publication : 2016 Article en page(s) : pp 65 – 94 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accès aux données
[Termes IGN] apprentissage profond
[Termes IGN] attribut sémantique
[Termes IGN] filtrage numérique d'image
[Termes IGN] jeu de données
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (auteur) Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper, we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture representations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another. Numéro de notice : A2016--151 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007%2Fs11263-015-0872-3 En ligne : https://doi.org/10.1007/s11263-015-0872-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85919
in International journal of computer vision > vol 118 n° 1 (May 2016) . - pp 65 – 94[article]Multifractal analysis for multivariate data with application to remote sensing / Sébastien Combrexelle (2016)
Titre : Multifractal analysis for multivariate data with application to remote sensing Type de document : Thèse/HDR Auteurs : Sébastien Combrexelle, Auteur ; Jean-Yves Tourneret, Directeur de thèse ; Steve Mclaughlin, Directeur de thèse Editeur : Toulouse : Université de Toulouse Année de publication : 2016 Importance : 211 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse, Spécialité Signal, Image, Acoustique et OptimisationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse fractale
[Termes IGN] analyse multivariée
[Termes IGN] approche hiérarchique
[Termes IGN] estimation bayesienne
[Termes IGN] image hyperspectrale
[Termes IGN] modèle statistique
[Termes IGN] télédétection
[Termes IGN] texture d'image
[Termes IGN] transformation en ondelettesRésumé : (auteur) Texture characterization is a central element in many image processing applications. Texture analysis
can be embedded in the mathematical framework of multifractal analysis, enabling the study of the fluctuations in regularity of image intensity and providing practical tools for their assessment, the wavelet coefficients or wavelet leaders. Although successfully applied in various contexts, multifractal analysis suffers at present from two major limitations. First, the accurate estimation of multifractal parameters for image texture remains a challenge, notably for small image sizes. Second, multifractal analysis has so far been limited to the analysis of a single image, while the data available in applications are increasingly multivariate. The main goal of this thesis is to develop practical contributions to overcome these limitations. The first limitation is tackled by introducing a generic statistical model for the logarithm of wavelet leaders, parametrized by multifractal parameters of interest. This statistical model enables us to counterbalance the variability induced by small sample sizes and to
embed the estimation in a Bayesian framework. This yields robust and accurate estimation procedures, effective both for small and large images. The multifractal analysis of multivariate images is then addressed by generalizing this Bayesian framework to hierarchical models able to account for the assumption that multifractal properties evolve smoothly in the dataset. This is achieved via the design of suitable priors relating the dynamical properties of the multifractal parameters of the different components composing the dataset. Different priors are investigated and compared in this thesis by means of numerical simulations conducted on synthetic multivariate multifractal images. This work is further completed by the investigation of the potential benefits of multifractal analysis and the proposed Bayesian methodology for remote sensing via the example of hyperspectral imaging.Note de contenu : Introduction
1- Multifractal analysis
2- Statistical model and univariate Bayesian estimation
3- Bayesian multifractal analysis of
multivariate imagesNuméro de notice : 25811 Affiliation des auteurs : non IGN Thématique : IMAGERIE/MATHEMATIQUE Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Spécialité : Signal, Image, Acoustique et Optimisation : Toulouse : 2016 Organisme de stage : Institut de Recherche en Informatique de Toulouse (I.R.I.T.) En ligne : http://www.theses.fr/2016INPT0078 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95074 Pointwise approach for texture analysis and characterization from very high resolution remote sensing images / Minh-Tan Pham (2016)
Titre : Pointwise approach for texture analysis and characterization from very high resolution remote sensing images Type de document : Thèse/HDR Auteurs : Minh-Tan Pham, Auteur ; Grégoire Mercier, Directeur de thèse Editeur : Université Bretagne Loire Année de publication : 2016 Importance : 177 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse pour obtenir le grade de Docteur de Telecom Bretagne, Mention : Sciences et Technologies de l'Information et de la Communication, en Informatique Traitement des imagesLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification
[Termes IGN] classification pixellaire
[Termes IGN] covariance
[Termes IGN] détection de changement
[Termes IGN] image à très haute résolution
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] matrice de covariance
[Termes IGN] segmentation d'image
[Termes IGN] texture d'image
[Termes IGN] théorie des graphes
[Termes IGN] viticultureIndex. décimale : THESE Thèses et HDR Résumé : (auteur) This thesis work proposes a novel pointwise approach for texture analysis in the scope of very high resolution (VHR) remote sensing imagery. This approach takes into consideration only characteristic pixels, not all pixels of the image, to represent and characterize textural features. Due to the fact that increasing the spatial resolution of satellite sensors leads to the lack of stationarity hypothesis in the acquired images, such an approach becomes relevant since only the interaction and characteristics of keypoints are exploited. Moreover, as this technique does not need to consider all pixels inside the image like classical dense approaches, it is more capable to deal with large-size image data offered by VHR remote sensing acquisition systems. In this work, our pointwise strategy is performed by exploiting the local maximum and local minimum pixels (in terms of intensity) extracted from the image. It is integrated into several texture analysis frameworks with the help of different techniques and methods such as the graph theory, the covariance-based approach, the geometric distance measurement, etc. As a result, a variety of texture-based applications using remote sensing data (both VHR optical and radar images) are tackled such as image retrieval, segmentation, classification, and change detection, etc. By performing dedicated experiments to each thematic application, the effectiveness and relevance of the proposed approach are confirmed and validated. Note de contenu : I- Introduction
II- Pointwise approach with graph theory
III- Pointwise approach with structural features
IV ConclusionNuméro de notice : 25815 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique Traitement des images : Telecom Bretagne : 2016 nature-HAL : Thèse DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-01464333v2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95080 Mapping slope movements in Alpine environments using TerraSAR-X interferometric methods / Chloé Barboux in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)
[article]
Titre : Mapping slope movements in Alpine environments using TerraSAR-X interferometric methods Type de document : Article/Communication Auteurs : Chloé Barboux, Auteur ; Tazio Strozzi, Auteur ; Reynald Delaloye, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 178 – 192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Alpes
[Termes IGN] analyse diachronique
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] mouvement de terrain
[Termes IGN] pente
[Termes IGN] Suisse
[Termes IGN] surveillance géologique
[Termes IGN] texture d'image
[Termes IGN] vitesseRésumé : (auteur) Mapping slope movements in Alpine environments is an increasingly important task in the context of climate change and natural hazard management. We propose the detection, mapping and inventorying of slope movements using different interferometric methods based on TerraSAR-X satellite images. Differential SAR interferograms (DInSAR), Persistent Scatterer Interferometry (PSI), Short-Baseline Interferometry (SBAS) and a semi-automated texture image analysis are presented and compared in order to determine their contribution for the automatic detection and mapping of slope movements of various velocity rates encountered in Alpine environments. Investigations are conducted in a study region of about 6 km × 6 km located in the Western Swiss Alps using a unique large data set of 140 DInSAR scenes computed from 51 summer TerraSAR-X (TSX) acquisitions from 2008 to 2012. We found that PSI is able to precisely detect only points moving with velocities below 3.5 cm/yr in the LOS, with a root mean squared error of about 0.58 cm/yr compared to DGPS records. SBAS employed with 11 days summer interferograms increases the range of detectable movements to rates up to 35 cm/yr in the LOS with a root mean squared error of 6.36 cm/yr, but inaccurate measurements due to phase unwrapping are already possible for velocity rates larger than 20 cm/year. With the semi-automated texture image analysis the rough estimation of the velocity rates over an outlined moving zone is accurate for rates of “cm/day”, “dm/month” and “cm/month”, but due to the decorrelation of yearly TSX interferograms this method fails for the observation of slow movements in the “cm/yr” range. Numéro de notice : A2015-863 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79249
in ISPRS Journal of photogrammetry and remote sensing > vol 109 (November 2015) . - pp 178 – 192[article]Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
[article]
Titre : Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas Type de document : Article/Communication Auteurs : Timothy Dube, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2015 Article en page(s) : pp 12 – 32 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] Afrique du sud (état)
[Termes IGN] biodiversité
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification
[Termes IGN] classification dirigée
[Termes IGN] espèce végétale
[Termes IGN] Eucalyptus dunii
[Termes IGN] Eucalyptus grandis
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] Pinus taeda
[Termes IGN] régression
[Termes IGN] sous-étage
[Termes IGN] sylviculture
[Termes IGN] texture d'imageRésumé : (auteur) The successful launch of the 30-m Landsat-8 Operational Land Imager (OLI) pushbroom sensor offers a new primary data source necessary for aboveground biomass (AGB) estimation, especially in resource-limited environments. In this work, the strength and performance of Landsat-8 OLI image derived texture metrics (i.e. texture measures and texture ratios) in estimating plantation forest species AGB was investigated. It was hypothesized that the sensor’s pushbroom design, coupled with the presence of refined spectral properties, enhanced radiometric resolution (i.e. from 8 bits to 12 bits) and improved signal-to-noise ratio have the potential to provide detailed spectral information necessary for significantly strengthening AGB estimation in medium-density forest canopies. The relationship between image texture metrics and measurements of forest attributes can be used to help characterize complex forests, and enhance fine vegetation biophysical properties, a difficult challenge when using spectral vegetation indices especially in closed canopies. This study examines the prospects of using Landsat-8 OLI sensor derived texture metrics for estimating AGB for three medium-density plantation forest species in KwaZulu Natal, South Africa. In order to achieve this objective, three unique data pre-processing techniques were tested (analysis I: Landsat-8 OLI raw spectral-bands vs. raw texture bands; analysis II: Landsat-8 OLI raw spectral-band ratios vs. texture band ratios and analysis III: Landsat-8 OLI derived vegetation indices vs. texture band ratios). The landsat-8 OLI derived texture parameters were examined for robustness in estimating AGB using linear regression, stepwise-multiple linear regression and stochastic gradient boosting regression models. The results of this study demonstrated that all texture parameters particularly band texture ratios calculated using a 3 × 3 window size, could enhance AGB estimation when compared to simple spectral reflectance, simple band ratios and the most popular spectral vegetation indices. For instance, the use of combined texture ratios yielded the highest R2 values of 0.76 (RMSE = 9.55 t ha−1 (18.07%) and CV-RMSE of 0.18); 0.74 (RMSE = 12.81 t ha−1 (17.72%) and CV-RMSE of 0.08); 0.74 (RMSE = 12.67 t ha−1 (06.15%) and CV-RMSE of 0.06) and 0.53 (RMSE = 20.15 t ha−1 (14.40%) and CV-RMSE of 0.15) overall for Eucalyptus dunii, Eucalyptus grandis, Pinus taeda individually and all species, respectively. Overall, the findings of this study provide the necessary insight and motivation to the remote sensing community, particularly in resource constrained regions, to shift towards embracing various texture metrics obtained from the readily-available and cheap multispectral Landsat-8 OLI sensor. Numéro de notice : A2015-849 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.002 Date de publication en ligne : 25/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79219
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 12 – 32[article]Color and texture interpolation between orthoimagery and vector data / Charlotte Hoarau in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)PermalinkLocal binary patterns and extreme learning machine for hyperspectral imagery classification / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkRandom Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features / Peijun Du in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)PermalinkDémélange d’images radar polarimétrique par séparation thématique de sources / Sébastien Giordano (2015)PermalinkPrédire la structure des forêts tropicales humides calédoniennes : analyse texturale de la canopée sur des images Pléiades / Elodie Blanchard in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkPermalinkSAR-SIFT : a SIFT-like algorithm for SAR images / Flora Dellinger in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkVisual accceptance of library-generated CityGML LOD3 building models / Ryan Garnett in Cartographica, vol 49 n° 4 (Winter 2014)PermalinkQuantification et cartographie de la structure forestière à partir de la texture des images Pléiades / Benoit Beguet in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)PermalinkSAR change detection based on intensity and texture changes / Maoguo Gong in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)Permalink