GLCM-based anisotropy estimation — the influence of computation parameters on the results
Christoph Georg Eichkitz, Johannes Amtmann · First Break · 2018
The grey level co-occurrence matrix (GLCM) is a second-order statistical texture classification method initially described by Haralick et al., (1973). Typically, two neighbouring images are compared by using a moving analysis window to construct a 2D GLCM. This is used subsequently in the calculation of GLCM-based attributes. Common applications of GLCM attributes include classification of satellite images (Franklin et al., 2001; Tsai et al., 2007) and images based on magnetic resonance or computed tomography (Kovalev et al., 2001; Zizzari et al., 2011). GLCM has played a minor role in seismic interpretation, but within the last 20 years several authors have used the GLCM method to interpret channels systems (Eichkitz et al., 2013, 2014, 2015a, 2015b, 2016; West et al., 2002; Gao, 2007, 2011; de Matos et al., 2011), sedimentary facies (Di and Gao, 2017; Eichkitz, et al., 2012; Chopra and Alexeev, 2005, 2006a, 2006b; Yenugu et al., 2010; Wang et al., 2016), salt bodies (Gao, 2003), and fractures (Eichkitz et al., 2015c, 2016; Schneider et al., 2016). Most of these studies focus on direct extraction of information from GLCM-based attributes.