We propose a novel processing protocol framework for neutron radiograph image quality improvement. Neutron radiographs
were collected at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR) CG-1B imaging station
utilizing a 2.35 Å cold neutron beam with flux ~107 n/cm2/sec. A 100 micron thick ZnS(Ag)/6LiF scintillator was coupled
via mirror to a second generation sCMOS camera system with 2k x 2k spatial resolution. We address image quality degradations
due to random spuriously detected gamma rays (spikes), camera dark current and readout noise (background), detection
system resolution fall-off with increasing spatial frequency, and Gaussian noise due to detection counting statistics. The
background is estimated and subtracted out. Gaussian noise is estimated and removed via 3D transform-domain collaborative
filtering to minimize effects of spatial resolution degradation. Spikes are removed via an adaptive morphological filter.
Capitalizing upon the resultant low noise images produced, Metz restoration filtering is employed to significantly improve
image sharpness with increasing spatial resolution. The order of operations for filtering is important, and we restore very low
noise images with ~70 micron resolution using our processing protocol.
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