A Novel Active Contours Model for Environmental Change Detection from Multitemporal Synthetic Aperture Radar Images.

Ahmadi, Salman et Homayouni, Saeid ORCID: https://orcid.org/0000-0002-0214-5356 (2020). A Novel Active Contours Model for Environmental Change Detection from Multitemporal Synthetic Aperture Radar Images. Remote Sensing , vol. 12 , nº 11. p. 1746. DOI: 10.3390/rs12111746.

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Résumé

In this paper, we propose a novel approach based on the active contours model for change detection from synthetic aperture radar (SAR) images. In order to increase the accuracy of the proposed approach, a new operator was introduced to generate a difference image from the before and after change images. Then, a new model of active contours was developed for accurately detecting changed regions from the difference image. The proposed model extracts the changed areas as a target feature from the difference image based on training data from changed and unchanged regions. In this research, we used the Otsu histogram thresholding method to produce the training data automatically. In addition, the training data were updated in the process of minimizing the energy function of the model. To evaluate the accuracy of the model, we applied the proposed method to three benchmark SAR data sets. The proposed model obtains 84.65%, 87.07%, and 96.26% of the Kappa coefficient for Yellow River Estuary, Bern, and Ottawa sample data sets, respectively. These results demonstrated the effectiveness of the proposed approach compared to other methods. Another advantage of the proposed model is its high speed in comparison to the conventional methods.

Type de document:	Article
Mots-clés libres:	SAR images; multitemporal; environmental change detection; active contours model
Centre:	Centre Eau Terre Environnement
Date de dépôt:	24 juill. 2020 13:30
Dernière modification:	08 févr. 2022 21:49
URI:	https://espace.inrs.ca/id/eprint/10340

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