Multidimensional data processing methods for material discrimination using an ideal X-ray spectrometric photon counting detector

Development at LETI of X-ray photon counting detectors based on CdTe/CZT architecture has shown many improvements in counting abilities and in energy resolution for fast digital imaging modalities. In this context, this study aims at quantifying contribution of these technologies associated to new data processing methods for radiographic material recognition in homeland security. An ideal spectrometric detector was simulated and three non-layered homogeneous materials at millimetric thicknesses were investigated as potential hazardous materials to identify. A criterion quantifying material separability was developed and appears applicable to various systems of detection. Two methods for exploiting spectrometric information were analyzed. The first one, named “channel binning method”, is based on spectrum data summation before the calculation of the attenuation coefficients. The second one, “linear method”, corresponds to a summation of the attenuation function after the log calculation, making the obtained data directly linear to material thickness. Both methods provide N data exploitable with the criterion of separability. Thresholds of the summation windows were optimized for N = 2 to 5 and, for N≥5, windows were selected equally distributed over the energy range of the spectrum. As reference, performances supplied by both methods were compared to an ideal integrating sandwich technology with an optimized geometry. Compared to sandwich detector performances, criterion values are increased by more than 50% using the “linear method” and the “channel binning method” with only two optimized summation windows (N=2). And, for an increasing number of summation windows, performances of both methods are enhanced. In the optimal configuration with windows width of 1 keV, both methods are identical, linear with material thickness and supply a gain of about 80% relatively to the sandwich detector, providing then higher performances than existing integrating technologies.