Image restoration by combining local genetic algorithm with adaptive pre-conditioning*

Abstract

Image restoration is an essential preprocessing step for many image analysis applications. For this issue, the most common problem is that some interesting structures in the image will be removed from the concerned image during noise suppression. Such interesting structures in an image often correspond to the discontinuities in the image. In this paper, we propose a novel efficient method for image restoration. The central idea in this method is to combine the hybrid genetic algorithm with adaptive pre-conditioning. 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. 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