Cellular LMS L-filters for noise suppression in still images and image sequences

A novel class of nonlinear adaptive L-filters based on cellular neural networks topology is presented. Like cellular neural systems and cellular automata as well, processing nodes, called cells, communicate with each other directly only through its nearest neighbors exchanging information. Each cell is an adaptive LMS L-filter. The proposed filters share the best features of both adaptive filters and cellular neural network topologies; their adaptive structure tracks image nonstationarities and their local interconnection feature makes it suitable for VLSI implementation. Cellular adaptive LMS L-filters are suited for high-speed parallel adaptive image filtering. Some interesting applications to image and image sequence filtering are demonstrated