Pixel Based Temporal Analysis Using Chromatic Property for Removing Rain from Videos

Abstract

The raindrops degrade the performance of outdoor vision system, and it brings difficulties for objects detection and analysis in image sequence. In this paper, we propose an algorithm detect moving objects using chromatic based properties in rain-affected videos captured by outdoor vision systems. Thus the raindrop removal algorithm includes two parts that is removal raindrops in background and removal raindrops in moving objects. Since the degradation made by raindrops is complex and appears as various changes. The raindrops detection function considering the chromatic properties of image sequence is induced, which does not need the velocity and time information of raindrops. Therefore, it is suitable for all the blur effects caused by raindrops. The removal raindrops are able to distinguish accurately the raindrops-affected pixels from the immovable or movable objects. Although the objects are moving in the rain, the algorithm is also effectual. The experiment results show that the proposal algorithm is able to remove the raindrops and improve the quality of image sequence remarkable.