A framework of single-image deraining method based on analysis of rain characteristics

In this paper, we propose an algorithm to remove rain streaks from single color image. Firstly, the guided filter, cooperated with rain pixels detection are used to separate a color image into low-frequency and high-frequency parts so that most rain components exist in the high-frequency part. Then, we focus on the high-frequency part to extract the non-rain details according to the characteristics of the rain in which a dictionary learning method is used. Meanwhile, to enhance the quality of the rain-removed image, the proposed principal direction of an image patch (PDIP) and the sensitivity of variance of color channels (SVCC) are employed in our work to help extract more non-rain details. Compared with the state-of-the-art works, our proposed method can remove the rain (especially heavy rain) from color images more efficiently.