A Variational Model for Image Denoising Corrupted by Poisson-Gaussian Noise

In order to improve the quality of recovered image, this paper proposes an image denoising algorithm based on variational model. Firstly, multiple-exposure imaging method is used to recovery radiance map which represents the linear response of light intensity. Simultaneously, Poisson-Gaussian noise modeling is introduced for modeling the degraded image. Afterwards, by making an analysis to the homogeneous patches of radiance map, a linear system of equations is derived to estimate the parameters of PoissonGaussian noise modeling. Moreover, following Bayes's rule and maximum a posteriori, a variational model yields to strictly convex function is derived which the optimal solution is the recover image. Eventually, Unknown parameters and the optimal solution are derived through least square method and steepest descent method respectively. Experiment results show that our algorithm is capable to remove noise from degraded image, meanwhile the detail and quality are guaranteed.