基于调制核回归和正则化Richardson-Lucy算法的中子图像复原方法

Neutron Imaging Restoration Method Based on Steering-kernel Regression and Regularized Richardson-Lucy Algorithm

  • 摘要: 由于中子成像系统中的诸多物理因素影响,使其得到的中子图像通常会发生严重的图像降质。本文将调制核回归(SK)引入到TV-RL算法中,提出了一种中子图像去模糊去噪方法SK-TV-RL,即基于SK的TV-RL算法。该方法能解决以往算法噪声放大的问题,并能复原降质图像中的细节信息。对比实验结果表明,无论基于客观评价还是主观评价,该方法都能有效地提高图像复原质量。

     

    Abstract: The neutron image obtained from neutron imaging system usually gets serious degradation because of the influence of physical constraints and other factors of the system. To solve this problem, by combining the steering-kernel regression (SK) with TV-RL algorithm, a neutron image restoration method SK-TV-RL was proposed. The method is capable of suppressing noise while restoring details of the blurred imaging results efficiently. Experimental results show that comparing with the other methods, the method can improve the restoration quality both visually and quantitatively.

     

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