Filtering combined dynamic stochastic resonance for enhancement of dark and low-contrast images

Dynamic stochastic resonance (DSR) based dark and low-contrast image enhancement has attracted more and more attention in recent years. For DSR based image enhancement, noise is essential and will be enhanced simultaneously with the contrast of the image, which is undesirable for improvement of perceptual quality. Nonlinear anisotropic diffusion (NAD) is one of the most widely used denoising methods due to good performance of edge preservation, but often fails for contaminated images with high level of noise. In this paper, we propose a novel partial differential equation method for image enhancement by introducing filtering into the stochastic resonance equation, and we consider two kinds of NAD filters. Numerical results demonstrate that the improved methods can not only increase brightness and contrast of the dark and low-contrast images efficiently by optimum iterations, but also remove the noise while preserving edges well, and therefore can achieve good perceptual quality.