Video derain is an important issue in the field of digital image processing and computer vision. This paper divides rain streaks into two types: one is rain in natural scenes, and the other is rain in stochastic scenes. In this paper, we propose a novel rotational video derain algorithm via nonconvex and nonsmooth algorithm (RoDerain). Not only can the rain streaks in natural scene be removed, but the rain streaks in stochastic scene can be also well removed. This paper added the rotation operator based on the discriminatively intrinsic priors of rain streaks and clean videos to remove the rain streaks in both natural and stochastic scenes.For the low rank problem of the background, we replace the solution of the nuclear norm with improved IRNN-Capped L₁ suitable for tensor. Finally,this paper used the Alternating Direction Method of Multipliers (ADMM) to optimize the solution of the proposed rain streaks removal algorithm model.The disadvantage is that global information is not considered. And the extensive experiment results show that our proposed algorithm performs favorably in comparison to several popular rain removal algorithms.

视频流失是数字图像处理和计算机视觉领域中的重要问题。本文将降​​雨条纹分为两种：一种是自然场景下的降雨，另一种是随机场景下的降雨。在本文中，我们通过非凸和非平滑算法（RoDerain）提出了一种新颖的旋转视频去漏算法。不仅可以去除自然场景中的雨水条纹，而且还可以很好地去除随机场景中的雨水条纹。本文基于有区别的内在先验性雨纹和清晰视频添加了旋转算子，以消除自然和随机场景中的雨纹。针对背景的低阶问题，我们用改进的IRNN代替核规范的解决方案封顶的L ₁适合张量。最后，本文使用乘数交替方向法（ADMM）对所提出的雨纹去除算法模型的求解进行了优化。缺点是没有考虑全局信息。大量的实验结果表明，与几种流行的除雨算法相比，我们提出的算法具有良好的性能。