Real Time Fog Removal Technique with Improved Quality through FFT

Images plays key role in all real world problems such as road or railway track images are used for traffic analysis. But images captured in open environment suffer from low contrast. When weather conditions are not good and clear, the light capture by the lens is spread by the atmosphere. Therefore conventional techniques for image enhancement are not enough to remove weather effects from captured images. The cloudy, foggy, or hazy weather conditions result as image color alteration and shrink the resolution and the contrast of the captured object in open-air. This work, analyze existing techniques used in image processing to remove bad weather effect. On the basis of this analysis this work proposes an efficient technique for more visibility from a grayscale and color images. This paper proposes an efficient and fast fog removal technique with quality enhancement. This method involves two phases. The first phase is used to remove fog from an image for which we are using a Fog removal technique based on prior knowledge. Second phase enhance quality of image for improved visibility and noise reduction using FFT (Fast Fourier Transformation). This method is efficient under a broad range of weather conditions including cloud, smog, fog etc.