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Video post processing: low-latency spatiotemporal approach for detection and removal of rain

机译：视频后期处理：低延迟时空方法，用于检测和去除雨水

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摘要

In this study, a novel, efficient and simple algorithm for detection and removal of rain from video using spatiotemporal properties is proposed. Advantageously, the spatiotemporal properties are involved to separate rain pixels from non-rain pixels. It is thus possible by way of the proposed algorithm to involve less number of consecutive frames, reducing the buffer size and delay. It works only on the intensity plane which further reduces the complexity and execution time significantly. This new algorithm does not assume the shape, size and velocity of raindrops which makes it robust to different rain conditions. Proposed method reduces the buffer size, which reduces the system cost, delay and power consumption. For performance evaluation, in addition to miss & false detection a new metric spatiotemporal variance is introduced. Results show that the proposed algorithm outperforms the other rain removal algorithms.
机译：在这项研究中，提出了一种新颖，有效且简单的算法，该算法利用时空特性检测和去除视频中的雨水。有利地，涉及时空特性以将雨像素与非雨像素分开。因此，通过所提出的算法，可以涉及更少数量的连续帧，从而减小缓冲器大小和延迟。它仅在强度平面上起作用，这进一步降低了复杂性和执行时间。该新算法未假定雨滴的形状，大小和速度，因此对不同的雨天条件均具有鲁棒性。提出的方法减小了缓冲区的大小，从而减少了系统成本，延迟和功耗。为了进行性能评估，除了遗漏和错误检测外，还引入了新的度量时空方差。结果表明，该算法优于其他的除雨算法。

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