Abstract
Dynamic weather effects such as rain cause rapid, distracting motion in a video sequence. This paper aims to remove rain and similar effects from video footage using a multi-step approach; Regions are identified as being potentially affected by rain if they exhibit a short-duration intensity spike. Falling rain drops are imaged by a video camera in a predictable way, as a streak with a consistent range of possible aspect ratios. To preserve scene motion, regions identified by this criterion are investigated, and those that do not fit into the expected range of aspect ratios are ignored. Information about the direction of rainfall is also used to reduce false detections. The effectiveness of this technique is shown on a number of video sequences. The method presented provides advantages over existing techniques.
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Hase, H., Miyake, K., Yoneda, M.: Real-time snowfall noise elimination. In: Proceedings of 1999 International Conference on Image Processing, ICIP 1999, vol. 2, pp. 406–409 (1999)
Starik, S., Werman, M.: Simulation of rain in videos. In: Texture Workshop, ICCV, vol. 2, pp. 406–409 (2003)
Barnum, P., Kanade, T., Narasimhan, S.: Spatio-temporal frequency analysis for removing rain and snow from videos. In: Workshop on Photometric Analysis For Computer Vision (2007)
Garg, K., Nayar, S.: Vision and rain. International Journal of Computer Vision 75, 3–27 (2007)
Zhang, X., Li, H., Qi, Y., Leow, W.K., Ng, T.K.: Rain removal in video by combining temporal and chromatic properties. In: IEEE International Conference on Multimedia and Expo 2006, pp. 461–464 (July 2006)
Foote, G.B., Du Toit, P.S.: Terminal Velocity of Raindrops Aloft. Journal of Applied Meteorology 8, 249–253 (1969)
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Brewer, N., Liu, N. (2008). Using the Shape Characteristics of Rain to Identify and Remove Rain from Video. In: da Vitoria Lobo, N., et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2008. Lecture Notes in Computer Science, vol 5342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89689-0_49
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DOI: https://doi.org/10.1007/978-3-540-89689-0_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89688-3
Online ISBN: 978-3-540-89689-0
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