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Rain Streak Removal with Well-Recovered Moving Objects from Video Sequences Using Photometric Correlation

机译:利用光度相关性,通过从视频序列的恢复恢复的移动物体去除雨条纹

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The main challenge in a rain removal algorithm is to differentiate rain streak from moving objects. This paper addresses this problem using the spa-tiotemporal appearance technique (STA). Although the STA-based technique can significantly remove rain from video, in some cases it cannot properly retain all the moving object regions. The photometric feature of rain streak was used to solve this issue. In this paper, a new algorithm combining STA and the photometric correlation between rain streak and background is proposed. Rain streak and moving objects were successfully detected and separated by combining both techniques, then fused to obtain well-recovered moving objects with rain-free video. The experimental results reveal that the proposed algorithm significantly outperforms the state-of-the-art methods for both real and synthetic rain streak.
机译:雨拆卸算法中的主要挑战是将雨条从移动物体区分开来。本文使用SPA-Tibporal外观技术(STA)来解决这个问题。虽然基于STA的技术可以显着从视频中取出雨水,但在某些情况下,它无法正确保留所有移动的物体区域。 Rain Streak的光度特征用于解决这个问题。本文提出了一种结合STA的新算法及雨条纹与背景之间的光度相关性。通过组合这两种技术成功地检测和分离雨条纹和移动物体,然后融合以获得与无雨视频的康复的移动物体。实验结果表明,该算法显着优于真实和合成雨条纹的最先进的方法。

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