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A FRAMEWORK OF SINGLE-IMAGE DERAINING METHOD BASED ON ANALYSIS OF RAIN CHARACTERISTICS

机译:基于雨雨特性分析的单图像辐射方法框架

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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.
机译:在本文中,我们提出了一种算法从单色图像中移除雨条纹。首先,使用雨像素检测的引导滤波器用于将彩色图像分离成低频和高频部分,使得大多数雨量部件存在于高频部分中。然后,我们专注于高频部分,根据使用字典学习方法的雨的特征来提取非雨细节。同时,为了增强雨雨图像的质量,在我们的工作中采用了图像贴片(PDIP)的所提出的图像贴片主体方向和颜色通道(SVCC)的差异的灵敏度,以帮助提取更多的非雨细节。与最先进的作品相比,我们所提出的方法可以更有效地从彩色图像中移除雨(特别是大雨)。

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