Classification-based material decomposition method for photon counting-based spectral radiography: Application to plastic sorting

Dual-energy X-ray radiography has been commonly used for materials separation. However, its performance is limited, especially for the separation of close materials or the identification of multiple materials. To cope with this problem, we propose to investigate the material decomposition ability of spectral radiography based on photon-counting detector. The latter having energy resolving capability can provide spectral information of several energy bins and thus enables selective imaging of multiple materials. In this framework, a classification-based patchwise regularized decomposition method was proposed to gain better differentiation between materials. It consists of performing several decompositions with reduced number of materials in the basis and classifying these decompositions using their cost function values. The results on simulations showed that, in the presence of Poisson noise, the method without classification can separate acrylonitrile-butadiene-styrene (ABS) from three kinds of flame retardants (FRs: brominated FR, chlorinated FR and phosphorus FR), but that the type of FR cannot be identified. With the classification technique, ABS and three kinds of FRs can be both separated and identified at the same time when the thickness was as large as 2 mm or 4 mm. The results on real data from physical photon-counting detector further confirm that the ABS, Br and Cl can be separated from each other.