Rain Removal from Videos using the Temporal- Spatial Statistical Properties

Abstract

Detection and removal of rain streaks from videos has recently become a great and challenging topic of research. This paper discusses a new technique for the removal of rain from videos using the temporal-spatial statistical properties. For this the temporal statistical properties of the pixels affected by rain are made use of, and then an efficient and easy algorithm is implemented which takes care of the effective removal of rain from videos. This technique works very well for videos with still and moving backgrounds involving moving objects with a fixed camera position. For the videos which involve the motion of the camera, the technique works well for a small rate of change of background in the camera frames. Our algorithm does not use variable and conditional parameters like the shape, size, velocity, and spatio-temporal physical model of raindrops, and camera’s parameters like the aperture, focal length, and exposure time. The test results quantitatively and qualitatively illustrate that the performance of our algorithm is quite efficient in comparison to the previously existing algorithms which are state of the art techniques used for the purpose of removing rain from videos.