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Multi-temporal image change mining based on evidential conflict reasoning / Fatma Haouas in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 59 - 75 Titre : Multi-temporal image change mining based on evidential conflict reasoning Type de document : Article/Communication Auteurs : Fatma Haouas, Auteur ; Basel Solaiman, Auteur ; Zouhour Ben Dhiaf, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 59 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] conflit d'intégration [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] raisonnement spatial [Termes descripteurs IGN] théorie de Dempster-Shafer [Termes descripteurs IGN] visibilité spatio-temporelle Résumé : (Auteur) Change detection monitoring on multi-temporal remote sensed images is a persistent methodological challenge where the Dempster-Shafer, or evidence, Theory (DST) has been often applied. This paper presents a new method based on the use of DST for mining bi-temporal remotely sensed images change. The main idea is based on the investigation, analysis and interpretation of different types of conflict between two bi-temporal mass distributions. The reasoning process is focused on the conflict significance and its “partial” causes. In fact, the global conflict that occurs during the joint exploitation of multi-temporal images gives general and non-sufficiently concise information. However, the partial conflict provides rich and important information with regards to the disagreement between knowledge sources. For computing the partial conflict between focal elements, the geometric representation of mass distributions is exploited. The obtained conflict measures, caused by change, are analyzed latter by a new algorithm for drifting binary change map and identifying change directions. The effectiveness and reliability of the proposed approach are shown through experimentations on simulated changed images as well as using multi-temporal Landsat satellite images where qualitative criteria as well as quantitative measures are applied. The performances of the proposed approach, in terms of changed area recognition, are compared to three different and widely used conflict measures: the Empty-set mass, the Jousselme’s distance and the Cosine measure. It is shown that the developed change detection approach outperforms these conflict measures. Numéro de notice : A2019-204 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.018 date de publication en ligne : 13/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.018 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92667 [article]

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