Generalized variation-based regularization algorithm for image reconstruction in high energy X-ray radiography

According to the characteristics of flash radiographic image with low signal-to-noise ratio, a generalized variation(GV) regularization based image reconstruction algorithm is proposed. In the new algorithm, p-norm is used as regularized term instead of total variation(TV) norm in widely-used TV-based image denoising methods. Then a smoothing functional is constructed for image reconstruction. Thus, the problem of image reconstruction is transformed to a problem of functional minimization. A nonlinear partial differential equation(PDE) is deduced from the new image reconstruction model. To solve the nonlinear PDE, fixed point iteration(FPI) scheme is introduced to linearize the PDE, ensuring the stability and convergence of regularized solution. Numerical results show that, compared with T