Spatio-temporal cellular automata-based filtering for image sequence denoising

This work describes a novel spatio-temporal cellular automata-based filtering algorithm (st-CAF) intended for performing image sequence denoising processes. The approach presents several advantages over more traditional single frame denoising techniques presented in the literature or even over their adaptation to sequences. Especially the fact that the cellular automaton used is able to contemplate information concerning the type of noise through the use of specific sequences to tune the algorithm, as well as temporal information by means of a spatio-temporal neighborhood when processing each pixel of the sequence. These two elements lead to significant improvements in the results with respect to simple spatial or temporal sets of neighbors.