Application of mixed models for solving the problem on restoring and estimating image parameters

Abstract

The text considers methods for estimating the parameters of autoregressive models of images. Special attention is given to estimating the internal autoregressions and its parameters in doubly stochastic image models. A procedure for estimating the constant parameters of autoregressive models according to the given type of model and to the real image is presented. We investigate whether it is possible to use the estimated parameters for image restoration. In addition we presents an algorithm for restoring images. This algorithm combines pseudogradient and nonlinear Kalman estimations. The efficiency of different procedures with respect to simulated and real images is analyzed.