Automatic extraction of lineaments based on wavelet edge detection and aided tracking by hillshade

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Automatic extraction of lineaments based on wavelet edge detection and aided tracking by hillshade

Xu, Junlong / Wen, Xingping / Zhang, Haonan / Luo, Dayou / Li, Jinbo / Xu, Lianglong / Yu, Min

Abstract Lineaments refer to the linear or curvilinear textures on remote sensing image, whose general spatial distribution characteristics are often the response of deep geological sturcture at the surface. Firstly, we use wavelet modulus maximum transformation to detect the edges with 4 scales on Landsat – 8 OLI B5 image and analyze their multi-scale characteristics. As the result, it is determined that the optimal scale of edge detection is 4, and the outline that consist of the edge pixels is roughly corresponding to the geological structure of mine area. Thus the incomplete lineaments have been extracted by using the 2D otsu algorithm. Secondly, the hillshade map generated based on DEM is processed to generate binarized linear shadow. Finally, the linear shadow is superimposed on the lineaments preliminarily extracted to obtain the optimized lineaments. Experiment results show that, based on the method, there are some deformation and displacement between the lineaments extracted and the actual geological structure, and it fail to effectively extract Qilinchang Fault, but lineaments are in good correspondence with Kuangshanchang Fault, Dongtou Fault and Niulan River Fault, which are basically in accord with the geological structure framework of the mine area.

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Dokumentinformationen

Titel :

Automatic extraction of lineaments based on wavelet edge detection and aided tracking by hillshade

Beteiligte:

Xu, Junlong (Autor:in) / Wen, Xingping (Autor:in) / Zhang, Haonan (Autor:in) / Luo, Dayou (Autor:in) / Li, Jinbo (Autor:in) / Xu, Lianglong (Autor:in) / Yu, Min (Autor:in)

Erschienen in:

Advances in Space Research ; 65 , 1 ; 506-517

Erscheinungsdatum :

2019-09-25

Format / Umfang :

12 pages

ISSN :

0273-1177

DOI :

https://doi.org/10.1016/j.asr.2019.09.045

Medientyp :

Aufsatz (Zeitschrift)