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Most outdoor applications such as surveillance, terrain classification and autonomous navigation require robust detection of image features. Under bad weather conditions, however, the contrast and colors of images are degraded and it is imperative to include mechanisms that overcome weather effects from images in order to make vision systems more reliable. Unfortunately it turns out that effects of weather cannot be overcome by simple image processing techniques. There are some existing methods to enhance contrast restoration in bad weather. Some of the methods provide contrast restoration but do not provide considerable visibility enhancement while other methods provide more visibility but do not maintain the color fidelity. A novel method is proposed in this paper that not only enhances visibility but also maintains the color fidelity. This method consists of three phases. The first two phases consists of estimating a measure of degradation and its removal while the final phase uses a novel wavelet fusion method to obtain the enhanced image. Performance analysis is carried out with the help of a contrast improvement index and sharpness measure. The experimental results on real images show the effectiveness of the approach.