Abstract: Stochastic resonance (SR) is a mechanism that noise can be added to the nonlinear system for transmitting the certain signals, and the output can be enhanced. In this paper, we propose an image denoising algorithm based on stochastic resonance of dynamical saturating nonlinear systems. Firstly, the image is resampled into one-dimensional signals, and the parameters of the saturating nonlinear system can be tuned optimally, then the SR effect can be obtained in the saturating nonlinear system. Comparing with the effect of the one-dimensional SR, the effect of image restoration of the two-dimensional SR is closer to the original image and it is showed that the effect of image enhancement of the two-dimensional SR is superior by the output histogram and peak signal-to-noise ratio (PSNR). Compared with traditional filtering methods, the denoising effect of the saturating nonlinear system is better and it is more robust to the change of noise intensity.

Key words: stochastic resonance, saturating nonlinear system, image denoising, grayscale image, peak signal to noise ratio