Detecting and characterizing lineaments using satellite images or digital elevation model data is a field of satellite image processing, providing a lot of useful information for geological structure analysis and mineral exploration. In recent years, many studies have been devoted to the identification of lineaments and their relationship with their distribution characteristics, geological structure and mineral deposit distribution.
Song Man Hyok, a section head at the Faculty of Earth Science and Technology, has proposed a new method for extracting the image features and lineaments related to the local extrema of an image or a digital elevation model (DEM) such as ridges and valleys, based on the continuous wavelet transform (CWT) of a set of variously illuminated hillshades.
The method is based on the principle that a hillshade can exactly reflect the lineaments nearly perpendicular to the illumination direction of the hillshade, but not other ones.
The method consists of four steps: (1) preparation of a set of differently illuminated hillshades of the input data, (2) detection of directional edges nearly perpendicular to the illumination direction from each hillshade based on the CWT, (3) a combination of multidirectional edges into an omnidirectional feature image, and (4) identification of lineaments through linkage and linearization of image feature lines.
He applied this method to the geological structure analysis of the study areas to provide a prerequisite for resource exploration and land development.
For detailed information, please refer to his paper “A Method to Extract Image Features and Lineaments Based on a Multi-hillshade Continuous Wavelet Transform” in “Mathematical Geosciences” (SCI).
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