Self-organizing map applied to image denoising

We treat self-organizing maps (SOMs) as means for denoising of images corrupted by multiplicative noise. To achieve this goal, we propose a scheme for blind source separation based on a nonlinear topology preserving mapping as it is performed by SOMs. Despite the assumption that only two noisy frames of the same image scene are available, we show that by a suitable post-processing step based on the estimates provided by the SOM, one can obtain enhanced versions of the originally noisy scenes. Our work is illustrated by application results of the proposed method to test and real images.