A phase space approach for detection and removal of rain in video

Abstract

Nowadays, the widespread use of computer vision algorithms in surveillance systems and autonomous robots has increased the demand for video enhancement algorithms. In this paper, we propose an algorithm based on phase congruency features to detect and remove rain and thus improve the quality of video. We make use of the following characteristics of rain streaks in video in order to detect them: (1) rain streaks do not occlude the scene at all instances, (2) all the rain streaks in a frame are oriented in a single direction, and (3) presence of rain streak at a particular pixel causes a positive change in intensity. Combining all these properties we are able to detect rain streaks in a particular frame using phase congruency features. The pixels in a frame which are identified as rain streaks are then replaced using the pixel information of its spatial and temporal neighbors which are not affected by rain. When this method is used in conjunction with phase correlation, we are able to remove rain of medium density from videos even when complex camera movement is involved.