Noise Level Estimation Method Based on PCA and BM3D for Neutron Image Denoising

To solve the problem of neutron image denoising, a noise level estimation method of weakening residual image eigenvalue was proposed. In this method, the principal component analysis (PCA) was utilized to analyze residual image eigenvalue and the noise level was estimated. According to the noise level, the image was denoised, and the residual image eigenvalue was weakened to acquire the final estimated noise level. The experimental results show that the proposed method can estimate the Gaussian noise level of the simulated image and the real neutron image, and achieve preferable denoising effect with high computational efficiency.