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A review of accuracy assesment for object-based image analysis: from per pixel to per-polygon approaches [review article] / Su Ye in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 141 (July 2018) . - pp 137 - 147 Titre : A review of accuracy assesment for object-based image analysis: from per pixel to per-polygon approaches [review article] Type de document : Article/Communication Auteurs : Su Ye, Auteur ; Robert Gilmore Pontius, Auteur ; Rahul Rakshit, Auteur Année de publication : 2018 Article en page(s) : pp 137 - 147 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image orientée objet [Termes IGN] classification automatique [Termes IGN] classification pixellaire [Termes IGN] échantillonnage de données [Termes IGN] estimation de précision [Termes IGN] polygone Résumé : (Editeur) Object-based image analysis (OBIA) has gained widespread popularity for creating maps from remotely sensed data. Researchers routinely claim that OBIA procedures outperform pixel-based procedures; however, it is not immediately obvious how to evaluate the degree to which an OBIA map compares to reference information in a manner that accounts for the fact that the OBIA map consists of objects that vary in size and shape. Our study reviews 209 journal articles concerning OBIA published between 2003 and 2017. We focus on the three stages of accuracy assessment: (1) sampling design, (2) response design and (3) accuracy analysis. First, we report the literature’s overall characteristics concerning OBIA accuracy assessment. Simple random sampling was the most used method among probability sampling strategies, slightly more than stratified sampling. Office interpreted remotely sensed data was the dominant reference source. The literature reported accuracies ranging from 42% to 96%, with an average of 85%. A third of the articles failed to give sufficient information concerning accuracy methodology such as sampling scheme and sample size. We found few studies that focused specifically on the accuracy of the segmentation. Second, we identify a recent increase of OBIA articles in using per-polygon approaches compared to per-pixel approaches for accuracy assessment. We clarify the impacts of the per-pixel versus the per-polygon approaches respectively on sampling, response design and accuracy analysis. Our review defines the technical and methodological needs in the current per-polygon approaches, such as polygon-based sampling, analysis of mixed polygons, matching of mapped with reference polygons and assessment of segmentation accuracy. Our review summarizes and discusses the current issues in object-based accuracy assessment to provide guidance for improved accuracy assessments for OBIA. Numéro de notice : A2018-286 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.002 Date de publication en ligne : 02/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90401 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018071	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018073	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018072	DEP-EAF	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]