Cellular Neural Network for Noise Cancellation of Gray Image Based on Hybrid Linear Matrix Inequality and Particle Swarm Optimization

In this paper, the technique of noise cancellation for gray image is presented by employing linear matrix inequality (LMI) and particle swarm optimization (PSO) based on cellular neural networks (CNN). A criterion for global asymptotic stability of CNN is presented based on the Lyapunov stability theorem, and the problem of image noise cancellation can be characterized in terms of LMIs. Based on stability conditions of LMI, the parameter of templates are obtained via PSO. The examples are given to illustrate the effectiveness of the proposed method.