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

作　　者：赵宗清 何卫华 王剑 郝轶丹 曹磊峰 谷渝秋 张保汉 

机构地区：[1]Science and Technology on Plasma Physics Laboratory [2]Laser Fusion Research Center,China Academy of Engineering Physics

出　　处：《Chinese Physics B》2013年第10期281-286,共6页中国物理B（英文版）

基　　金：Project supported by the National High-Tech ICF Committee of China,Foundation of China Academy of Engineering Physics(Grant Nos.2009A0102003 and 2011B0102021);the National Natural Science Foundation of China(Grant No.10905051)

摘　　要：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.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.

关 键 词：inertial confinement fusion coded imaging DECONVOLUTION Gaussian distribution MAXIMUM-LIKELIHOOD 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TL632[自动化与计算机技术—计算机科学与技术]