Efficient moving objects detection by LIDAR for rain removal

Abstract

Rain and snow are often imaged as brighter streaks, which can not only confuse human vision but degrade efficiency of computer vision algorithm. Rain removal is very important technique in these fields such as video surveillance and automatic driving. Most existing methods rely on optical flow algorithm to detect rain pixel and estimate motion field. However, it is extremely challenging for them to achieve real-time performance. In this paper, a LIDAR based algorithm is proposed, which is capable of achieving rain pixel robustly and efficiently from motion field. The motion objects (vehicles and human) are identified for separation by LIDAR (Sick LMS200) in this paper. Then rain pixels on moving objects are removed by bilateral filter which can preserve edge information instead of causing blurring artifacts around rain streaks. Experimental results show that our method significantly outperforms the previous methods in removing rain pixel and detecting motion objects from motion field.