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