A new Bayesian approach to image denoising with a combination of MRFs and pixon method

In this paper, we propose a novel pixon-based multiresolution method for image denoising. The key idea to our approach is that a pixon map is embedded into the MRF models under a Bayesian framework. The remarkable advantage of our approach over the existing works in this field is that restoring corrupted images and preserving the shape transitions in the restored results have been orchestrated very well. A simulated annealing algorithm is implemented to find the MAP solution. A lot of experiments illustrate that our method is much more effective and powerful in the noise reduction than the Wiener and median filtering techniques, two typical and widely used techniques.