Introduction - If you have any usage issues, please Google them yourself
Abstract—A novel algorithm to remove rain or snow streaks
a video sequence using temporal correlation and low-rank
matrix completion is proposed in this paper. Based on the
observation that rain streaks are too small and move too fast
to affect the optical flow estimation between consecutive frames,
we obtain an initial rain map by subtracting temporally warped
frames a current frame. Then, we decompose the initial
rain map into basis vectors based on the sparse representation,
and classify those basis vectors into rain streak ones and outliers
with a support vector machine. We then refine the rain map
by excluding the outliers. Finally, we remove the detected rain
streaks by employing a low-rank matrix completion technique.
Furthermore, we extend the proposed algorithm to stereo video
deraining. Experimental results demonstrate that the proposed
algorithm detects and removes rain or snow streaks efficiently,
outperforming conventional algorithms.