Comparative analysis of video signal filtering quality by various nonlinear methods in nonstationary mode

Abstract

The paper focuses on solution of tasks of optimal nonlinear filtering in the Gaussian approximation, synthesis of the quasi-optimal reception algorithm for collaborative filtering the continuous and discrete Markov processes and the simplified nonlinear filtering algorithm for the two-dimensional continuous Markov processes describing video signals and noise in a nonstationary mode. The signal is presented as a sum of the multi-dimensional continuous Markov process and one-dimensional discrete Markov process. The quality was estimated with digital simulation of processing the mixture of video signal, Johnson noise, and white Gaussian noise. It is shown that the use of the collaborative nonlinear filtering algorithm for continuous and discrete Markov processes allows improving quality of the compromising emanation filtering in comparison with two-dimensional filtering algorithm for all kinds of noise. However, this is difficult to realize it in practice.