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In addition to the widely used monochromatic X-ray source, the polychromatic X-ray source may also be used in many cases of propagation-based phase-contrast imaging (PB-PCI). It is not sufficient to investigate the optimization procedure only for the monochromatic applications. The focus of this paper is to investigate the effects of spectrum and imaging geometry on the image quality of PB-PCI, for applications involving propagation in vacuum and air. The quality of phase contrast image has been quantitatively characterized by using contrast and SNR as quality metrics in this paper. The optimal geometry has been investigated in three situations, where four cases are considered. Based on the numerical simulation, it is observed that the contrast and SNR in the case of polychromatic X-ray are lower than the monochromatic X-ray. Therefore, the influence of the X-ray spectrum on the contrast and SNR must not be neglected. The contrast in the case of polychromatic X-ray, and the SNR in both polychromatic and monochromatic X-ray, is lower for propagation in air compared to the propagation in vacuum. Evidently, the air absorption is an important factor in the propagation-based phase-contrast imaging. The experimental and numerical results for all three situations are presented to verify the effect of the geometry on the image quality in the air condition. It is found that the experimental results confirm the validity of numerical results for both the quality metrics. The object specification and the X-ray scattering have obvious influence on the image quality, as seen in the experimental results.

Neutron penumbral imaging is a significant diagnostic technique in laser-driven inertial confinement fusion experiment. It is very important to develop a new reconstruction method to improve the resolution of neutron penumbral imaging. A new nonlinear reconstruction method based on total variation (TV) regularization is proposed in this paper. A TV-norm is used as regularized term to construct a smoothing functional for penumbral image reconstruction in the new method, in this way, the problem of penumbral image reconstruction is transformed to the problem of a functional minimization. In addition, a fixed point iteration scheme is introduced to solve the problem of functional minimization. The numerical experimental results show that, compared to linear reconstruction method based on Wiener filter, the TV regularized nonlinear reconstruction method is beneficial to improve the quality of reconstructed image with better performance of noise smoothing and edge preserving. Meanwhile, it can also obtain the spatial resolution with 5 μm which is higher than the Wiener method.