Particle Swarm Optimization for Gray-Scale Image Noise Cancellation

In this paper, the control of analog cellular neural network systems via particle swarm optimization (PSO) approach is presented. A novel method for designing templates of a cellular neural network for gray-scale image noise cancellation is discussed. Based on the PSO method, this approach is used to design the templates of a cellular neural network and diminish the noise interference in polluted images. Finally, the demonstrated examples are presented to illustrate the effectiveness of the proposed PSO -CNN methodology.