A framework of single-image deraining method based on analysis of rain characteristics
Yinglong Wang, Chen Chen, Shuyuan Zhu, Bing Zeng · 2016
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.