X-ray computed tomography (CT) is a non-destructive technique allowing the visualization of sample internal structure. A medical CT scanner consists in an X-ray source and a detector, which face each other and rotate around the sample. Bi-dimensional radiographic projections are acquired at various angles from 0° to 360° and then processed by a mathematical algorithm (i.e., image reconstruction) in order to obtain a 3D visualization of the object. Different types of image reconstructions exist, including the widely used filtered backprojection that requires little computational resources but produces less qualitatively accurate images, and iterative reconstruction, based on time consuming and numerically intensive algorithm but providing better images quality (Bushberg et al., 2012).The images are displayed in a gray scale related to the X-ray attenuation by the sample materials (Rizescu et al., 2001).Initially, this technology was developed for medical imaging, but its potential for other domains was rapidly understood (Mees et al., 2003).This paper explores a specific CT methodology, called dual-energy CT scanning (DECT), elaborated for the first time in the seventies by Alvarez and Makovski (1976). The technique consists in imaging objects with two different X-ray spectra and in combining the results to achieve various objectives, including one allowing the discrimination and identification of materials based on their density and elemental composition. From a physical perspective, DECT exploits the energy dependence of photoelectric absorption and Compton scattering