A new method for parameter estimation of edge-preserving regularization in image restoration

In image restoration, the so-called edge-preserving regularization method is used to solve an optimization problem whose objective function has a data fidelity term and a regularization term, the two terms are balanced by a parameter λ . In some aspect, the value of λ determines the quality of images. In this paper, we establish a new model to estimate the parameter and propose an algorithm to solve the problem. In order to improve the quality of images, in our algorithm, an image is divided into some blocks. On each block, a corresponding value of λ has to be determined. Numerical experiments are reported which show efficiency of our method.