Contrast Restoration Of Foggy Weather Images

Images captured by some monitor systems in foggy weather are always low quality, such as noisy, blurred and mainly poor contrast. The research of restoring these images is of great significance to ensure that those sets would get better images and the traffic system would be well-balanced. There are many techniques for image enhance and restoration presently. In this thesis, we compare and analyze the traditional space invariant image-processing techniques, and find that those techniques are not sufficient to remove foggy weather effects and to restore contrast, and that the restoration with depth is the key point. Then we show the principle of restoring technique, which uses an atmospheric-physics based model and its application condition. By questing for the proper detail methods and improving them, the experimental results show clearly that this technique filters well the foggy images and the image contrast is restored well.