Extraction of Edge-type and Anomaly-type Lineaments Based on Directional Continuous Wavelet Transform

Abstract

ABSTRACT
Background
Lineaments can be expressed as linear features which are notably brighter or darker than background (anomaly-type) and suddenly changed in brightness (edge-type) in the remote sensing (RS) and digital elevation model (DEM) images. A new method is proposed to extract both types of lineaments from RS and DEM images based on directional continuous wavelet transform (CWT).
The method consists of three steps: (i) determination of omni-directional CWT coefficient concerned with image gradient magnitude and omni-direction image reflecting image gradient direction using multi-directional CWT coefficients, (ii) extraction of image features such as extrema and edges using CWT modulus maxima line and (iii) detection of lineaments through segmentation and linkage of image features and linearization of image feature segments. The omni-directional CWT and omni-direction image determined from multi-directional CWT coefficients are associated with image gradient to be applied to image feature extraction, segmentation and linkage. The positive and negative lineaments can also be detected by the method.
The proposed method is tested using a simple example image and compared with the Hough transform (HT) method and applied to real RS and DEM images to extract both types of lineaments, which are compared with real geological structures including faults. The results show the proposed method is superior to the HT method and effective in detection of lineaments reflecting geological structures which are roughly rectilinear and expressed at multiple scales and directions.