Object composition identification via mediated-reality supplemented radiographs

This exploratory work investigates the feasibility of extracting linear attenuation functions with respect to energy from a multi-channel radiograph of an object of interest composed of a homogeneous material by simulating the entire imaging system combined with a digital phantom of the object of interest and leveraging this information along with the acquired multi-channel image. This synergistic combination of information allows for improved estimates on not only the attenuation for an effective energy, but for the entire spectrum of energy that is coincident with the detector elements. Material composition identification from radiographs would have wide applications in both medicine and industry. This work will focus on industrial radiography applications and will analyse a range of materials that vary in attenuative properties. This work shows that using iterative solvers holds encouraging potential to fully solve for the linear attenuation profile for the object and material of interest when the imaging system is characterized with respect to initial source x-ray energy spectrum, scan geometry, and accurate digital phantom.