Abstract
Since the first application of neutron radiography in the 1930s, the field of neutron radiography has matured enough to develop several applications. However, advances in the technology are far from concluded. In general, the resolution of scintillator-based detection systems is limited to the $10\mu m$ range, and the relatively low neutron count rate of neutron sources compared to other illumination sources restricts time resolved measurement. One path toward improved resolution is the use of magnification; however, to date neutron optics are inefficient, expensive, and difficult to develop. There is a clear demand for cost-effective scintillator-based neutron imaging systems that achieve resolutions of $1 \mu m$ or less. Such imaging system would dramatically extend the application of neutron imaging. For such purposes a coded source imaging system is under development. The current challenge is to reduce artifacts in the reconstructed coded source images. Artifacts are generated by non-uniform illumination of the source, gamma rays, dark current at the imaging sensor, and system noise from the reconstruction kernel. In this paper, we describe how to pre-process the coded signal to reduce noise and non-uniform illumination, and how to reconstruct the coded signal with three reconstruction methods correlation, maximum likelihood estimation, and algebraic reconstruction technique. We illustrates our results with experimental examples.
