R-L Method and BLS-GSM Denoising for Penumbra Image Reconstruction

When neutron yield is very low, reconstruction of coding penumbra image is rather difficult. In this paper, low-yield (10 ⁹ ) 14 MeV neutron penumbra imaging was simulated by Monte Carlo method. The Richardson Lucy (R-L) iteration method was proposed to incorporated with Bayesian least square-Gaussian scale mixture model (BLS-GSM) wavelet denoising for the simulated image. Optimal number of R-L iterations was gotten by a large number of tests. The results show that compared with Wiener method and median filter denoising, this method is better in restraining background noise, the correlation coefficient R _sr between the reconstructed and the real images is larger, and the reconstruction result is better.