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Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective / Mohammad D. Hossain in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 115 - 134 Titre : Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective Type de document : Article/Communication Auteurs : Mohammad D. Hossain, Auteur ; Dongmei Chen, Auteur Année de publication : 2019 Article en page(s) : pp 115 - 134 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image orientée objet [Termes IGN] appariement de données localisées [Termes IGN] apprentissage automatique [Termes IGN] classification hybride [Termes IGN] image à haute résolution [Termes IGN] objet géographique [Termes IGN] segmentation d'image [Termes IGN] segmentation en régions [Termes IGN] segmentation par décomposition-fusion Résumé : (Auteur) Image segmentation is a critical and important step in (GEographic) Object-Based Image Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly dependent on the quality of image segmentation. Segmentation has been used in remote sensing image processing since the advent of the Landsat-1 satellite. However, after the launch of the high-resolution IKONOS satellite in 1999, the paradigm of image analysis moved from pixel-based to object-based. As a result, the purpose of segmentation has been changed from helping pixel labeling to object identification. Although several articles have reviewed segmentation algorithms, it is unclear if some segmentation algorithms are generally more suited for (GE)OBIA than others. This article has conducted an extensive state-of-the-art survey on OBIA techniques, discussed different segmentation techniques and their applicability to OBIA. Conceptual details of those techniques are explained along with the strengths and weaknesses. The available tools and software packages for segmentation are also summarized. The key challenge in image segmentation is to select optimal parameters and algorithms that can general image objects matching with the meaningful geographic objects. Recent research indicates an apparent movement towards the improvement of segmentation algorithms, aiming at more accurate, automated, and computationally efficient techniques. Numéro de notice : A2019-138 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.009 Date de publication en ligne : 23/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.009 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92469 [article]

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081-2019041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2019043	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2019042	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

An unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images / Su Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 8 (August 2015)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 8 (August 2015) . - pp 637 - 645 Titre : An unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images Type de document : Article/Communication Auteurs : Su Ye, Auteur ; Dongmei Chen, Auteur Année de publication : 2015 Article en page(s) : pp 637 - 645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] classification non dirigée [Termes IGN] détection de changement [Termes IGN] image multibande [Termes IGN] luminance lumineuse [Termes IGN] milieu urbain [Termes IGN] saturation de la couleur Résumé : (auteur) Unsupervised change detection techniques have been widely employed in the remote-sensing area when suitable reference data is not available. Image (or Index) differencing is one of the most commonly used methods due to its simplicity. However, past applications of image differencing were often inefficient in separating real change and noise due to the lack of steps for feature selection and integration of contextual information. To address these issues, we propose a novel unsupervised procedure which uses two complementary features, namely luminance and saturation, extracted from multispectral images, and combines T-point thresholding, Bayes fusion, and Markov Random Fields. Through a case study, the performance of our proposed procedure was compared with other three unsupervised changedetection methods including Principle Component Analysis (PCA), Fuzzy c-means (FCM), and Expectation Maximum-Markov Random Field (EM-MRF). The change detection results from our proposed method are more compact with less noise than those from other methods over urban areas. The quantitative accuracy assessment indicates that the overall accuracy and Kappa statistic of our proposed procedure are 95.1 percent and 83.3 percent, respectively, which are significantly higher than the other three unsupervised change detection methods Numéro de notice : A2015-982 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.8.637 En ligne : http://dx.doi.org/10.14358/PERS.81.8.637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80253 [article]

Change detection from remotely sensed images: From pixel-based to object-based approaches / Masroor Hussain in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 91 - 106 Titre : Change detection from remotely sensed images: From pixel-based to object-based approaches Type de document : Article/Communication Auteurs : Masroor Hussain, Auteur ; Dongmei Chen, Auteur ; Angela Cheng, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 91 - 106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse spectrale [Termes IGN] classification orientée objet [Termes IGN] classification pixellaire [Termes IGN] détection de changement [Termes IGN] exploration de données géographiques [Termes IGN] télédétection Résumé : (Auteur) The appetite for up-to-date information about earth’s surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection Numéro de notice : A2013-299 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.03.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.03.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32437 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013061	RAB	Revue	Centre de documentation	En réserve L003	Disponible