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Computer vision-based framework for extracting tectonic lineaments from optical remote sensing data / Ehsan Farahbakhsh in International Journal of Remote Sensing IJRS, vol 41 n°5 (01 - 08 février 2020)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 41 n°5 (01 - 08 février 2020) . - pp 1760 - 1787 Titre : Computer vision-based framework for extracting tectonic lineaments from optical remote sensing data Type de document : Article/Communication Auteurs : Ehsan Farahbakhsh, Auteur ; Rohitash Chandra, Auteur ; Hugo K. H. Olierook, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1760 - 1787 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Australie occidentale (Australie) [Termes IGN] cartographie géologique [Termes IGN] détection de contours [Termes IGN] digue [Termes IGN] faille géologique [Termes IGN] filtre [Termes IGN] image Landsat-8 [Termes IGN] linéament [Termes IGN] tectonique [Termes IGN] vision par ordinateur Résumé : (auteur) The extraction of tectonic lineaments from digital satellite data is a fundamental application in remote sensing. The location of tectonic lineaments such as faults and dykes are of interest for a range of applications, particularly because of their association with hydrothermal mineralization. Although a wide range of applications have utilized computer vision techniques, a standard workflow for application of these techniques to tectonic lineament extraction is lacking. We present a framework for extracting tectonic lineaments using computer vision techniques. The proposed framework is a combination of edge detection and line extraction algorithms for extracting tectonic lineaments using optical remote sensing data. It features ancillary computer vision techniques for reducing data dimensionality, removing noise and enhancing the expression of lineaments. The efficiency of two convolutional filters are compared in terms of enhancing the lineaments. We test the proposed framework on Landsat 8 data of a mineral-rich portion of the Gascoyne Province in Western Australia. To validate the results, the extracted lineaments are compared to geologically mapped structures by the Geological Survey of Western Australia (GSWA). The results show that the best correlation between our extracted tectonic lineaments and the GSWA tectonic lineament map is achieved by applying a minimum noise fraction transformation and a Laplacian filter. Application of a directional filter shows a strong correlation with known sites of hydrothermal mineralization. Hence, our method using either filter can be used for mineral prospectivity mapping in other regions where faults are exposed and observable in optical remote sensing data. Numéro de notice : A2020-464 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01431161.2019.1674462 Date de publication en ligne : 11/10/2019 En ligne : https://doi.org/10.1080/01431161.2019.1674462 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94902 [article]