Nonlinear Bistable Stochastic Resonance Filters for Image Processing

Nonlinear bistable double-well stochastic resonance systems have been successfully used for one-dimensional signal processing, based on the concept of parameter-tuning stochastic resonance. This paper investigates the applications of parameter-tuning stochastic resonance in image processing. First, a two-dimensional stochastic resonance system is introduced as a nonlinear filter for image processing. The equation satisfied by the dynamic probability density function of the images processed by this stochastic resonance filter and its solutions are then discussed. Finally, this nonlinear filter is used to process a black-white image corrupted by additive white Gaussian noise to reveal the possibility to extend the concept of parameter-tuning stochastic resonance to two-dimensional cases. This provides an innovative approach for image processing.