An Efficient Deblurring Algorithm on Foggy Images using Curvelet Transforms

The contrast and color of an image will be degraded if the photographs are taken under poor weather conditions e.g. rain and fog. Added to this, if in a scene motion blur is also there then apart from the degradation of contrast and color the complexity of the image due to blur is also increased. In this paper we have compared certain deblurring algorithm and also implemented de-weathering algorithm with the help of curvelets, after rectifying the motion blur of the given scene. Experimental results presented in this paper show that the Cumulative Probability of Blur Detection (CPBD) values are better for the results obtained using the algorithms of deblurring with curvelets, instead of only using deblurring. Hence it can be concluded that the algorithm presented performs better than the algorithm where motion blur was rectified in a foggy condition without using curvelets.