Weighted image defogging method using statistical RGB channel feature extraction

In this paper, we present a weighted adaptive image defogging method by extracting features in the RGB color channels. We adaptively detect an atmospheric light through undesired fog in the dark channel prior obtained in the YCbCr color channels and generate a transmission map based on the detected atmospheric light. We adaptively remove the fog by applying the color correction algorithm based on the feature extraction in the RGB color channels. The proposed algorithm can overcome the problem of local color distortion, which is known to be the limitations of existing defogging techniques. Experimental results demonstrate that the proposed algorithm can remove image degradation caused by fog, clouds, smoke, and dust in digital imaging devices.