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

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.