An improved deconvolution method for X-ray coded imaging in inertial confinement fusion

In inertial confinement fusion (ICF), X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson–Lucy (RL) method has a strong ability to deblur the image where the noise follows the Poisson distribution. However, it always suffers from over-fitting and noise amplification, especially when the signal-to-noise ratio of image is relatively low. In this paper, we propose an improved deconvolution method for X-ray coded imaging. We model the image data as a set of independent Gaussian distributions and derive the iterative solution with a maximum-likelihood scheme. The experimental results on X-ray coded imaging data demonstrate that this method is superior to the RL method in terms of anti-overfitting and noise suppression.