Coding and sampling for compressive x-ray diffraction tomography

Coded apertures and energy resolving detectors may be used to improve the sampling efficiency of x-ray tomography and increase the physical diversity of x-ray phenomena measured. Coding and decompressive inference enable increased molecular specificity, reduced exposure and scan times. We outline a specific coded aperture x-ray coherent scatter imaging architecture that demonstrates the potential of such schemes. Based on this geometry, we develop a physical model using both a semi-analytic and Monte Carlo-based framework, devise an experimental realization of the system, describe a reconstruction algorithm for estimating the object from raw data, and propose a classification scheme for identifying the material composition of the object at each location.