Rain detection and removal from slowly varying background videos

Prusty, Pankaj; Mohanty, Bibhuprasad

doi:10.47974/JSMS-961

Open Access Research Article

Rain detection and removal from slowly varying background videos

Pankaj PrustyDepartment of Electronics and Communications EngineeringSiksha ‘O’ Anusandhan (Deemed to be University), Khandagiri, Bhubaneswar, OdishaIndiaView full profile → , ^*Bibhuprasad MohantyCorresponding authorbibhumohanty@soa.ac.inDepartment of Electronics and Communications EngineeringSiksha ‘O’ Anusandhan (Deemed to be University), Khandagiri, Bhubaneswar, OdishaIndiaView full profile →

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pp. 225–239Vol. 26Issue 1December 2022DOI: 10.47974/JSMS-961XML

Published Online:: 31 Dec 2022
Article type:: Research Article
Language:: EN
Article no.:: JSMS-961
Pages:: 225–239

Abstract

Rain in bad weather becomes very challenging issue for automated driver assistance systems, security applications and many other computer vision algorithms. Number of rain removal algorithms have been proposed in these years but none of them has been able to increase the accuracy to large extent. In this paper a novel algorithm has been proposed where the slowly varying back ground scenes are taken for analysis. One part of the algorithm is based on the detection of rain pixels and the other part is removing them such that the original image must not lose its originality. Initially one background is modelled by taking the intensities of neighbourhoods of pixels. Then rain is detected by comparing each pixel with the modelled back ground followed by updating the background. The detected rain pixels are repaired with the help of some temporal neighbours. The results are promising to prove the work.

Keywords

Rain Temporal correlation Background modelling

Subject Classifications

68T05 Learning and adaptive systems in artificial intelligence

References

[1] Gunn, R., Kinzer, G.D., “Terminal Velocity for Water Droplet in Stagnant Air” Journal of Meteorology, 1949, 6, pp.243-248.
[2] Beard, K.V., Chuang, C.H., “A New model for the equilibrium Shape of Rain Drops”, Journal of Atmospheric Science, 1987, 44(11), pp.1509-1524.
[3] Marshall, J.S, Palmer, W.M.K,. “The Distribution of Raindrops with Sizes” Journal of Meteorology 1948, 5, pp.165–166.
[4] Manning, R.M., “Stochastic Electromagnetic Image Propagation”, McGraw-Hill, Inc, 1993.
[5] Wang, T., Clifford, R.S., “Use of Rainfall-Induced Optical Scintillations to Measure Path-Averaged Rain Parameters”, 1975, 8, pp:927–937.
[6] Tripathi, A. K. and Mukhopadhyay, S.,”A probabilistic Approach for Detection and Removal of Rain from Videos” , IETE Journal of Research, 2011, 57, pp:82-91.
[7] Starik, S. and Werman, m,: “Simulation of rain in videos” , Proceedings of Texture: The 3rd international workshop on Texture Analysis and Synthesis, France, 2003, pp.95-100.
[8] Tripathi,A.K. and Mukhopadhyay, S., “Rain Rendering in Videos”, 4th International Conference On Computer Applications in Electrical Engineering Recent Advances, India, February 2010.
[9] Zhang, X., Li, H., Qi, Y., Kheng, L., Khim, T, “Rain Removal in video by combining temporal and chromatic properties”, International Conference on Multimedia Computing and Systems, 2006.
[10] Garg, K., Nayar, S.K., “detection and removal of rain from videos”, IEEE computer society conference on Computer vision and pattern Recognition, 2004, 1, pp:528-535.
[11] Shen, M., Xue, P., “A Fast Algorithm for rain detection and removal from videos”, IEEE International Conference on Multimedia Computing and Systems, 2011.
[12] Barnum, P., Kanade, T., Narasimhan, S., “Spatio-Temporal Frequency Analysis for Removing Rain and Snow from Videos”, Proceedings of Workshop on Photometric Analysis For Computer Vision (PACV), in conjunction with ICCV, 2007.
[13] Bahnsen, C., Moeslund, T., “Rain Removal in Traffic Survellance: Does it Matter?”, IEEE Transaction on Intelligent Transportation Systems, 2019, 20(8), pp.2802-2819.
[14] Wang, Y., Liu, S., Xie, D., Zeng, B., “Removing Rain Streaks by Linear Model”, ,IEEEAcess, 2020, 8, pp:54802-54815.
[15] Kumar, S., Gupta, A., Jha, R.K., “Analysis Diagnosis and Correction of Rain Streaks”, TENCON-2019-2019 IEEE Region 10 Conference.
[16] Tang, H., Zhu, L., Zhang, D., Wang, X., “Single image rain removal using pure rain dictionary learning”, IET Image Processing,1019, 13(10), pp:1797-1804.
[17] Xiao, J., Zou, W., Chen, Y., Wang, W., Lei, J., “Single image rain removal based on depth field and sparse coding”, Pattern recognition Letters, 2018, 116, pp:212-217.
[18] Chen, J., Chau, L., “A Rain Pixel Recovery Algorithm for videos With Highly Dynamic Scenes”, IEEE Transactions on Image Processing, 2014, 23(3), pp:1097-1104.
[19] Li, P., Tian, J.,Wang,G., Wu, C., “Model-Based Deep Network for Single Image Deraining”, IEEE Access, 2020, 8, 14036 – 14047.
[20] Pak, K., Kim, M., Lim, H., Yu, S., Paik, J., “Fast rain Removl Using Rain Map and Temporal Filtering for Consumer Imaging Applications” IEEE 8th International Conference on Consumer Electronics 2018.
[21] E,Alaa, Hakim, A., “A Novel Approach for Rain Removal from Videos Using Low-Rank Recovery” 5th IEEE International Confference on Intelligent Systems, Modelling and Simulation. 2014.
[22] Prusty,P., Nayak, J., “Detection and Removal of Rain from satic Background videos”, 2015, International Journal of Applied Engineering and Research,10(9), pp.22791-22797.
[23] Samantaray,A., Kanungo, P., Mohanty,B., “Neighborhood decision based impulse noise filter”, 2018, IET Image Processing,12(7), pp.1222-1227.
[24] H.Hove, “Evaluation of statistical methods for assessing reliability from degradation data : A simulation study”, Journal of Statistics and Management Systems, Vol 24, Issue 6, 2021.
[25] A. Tadesse, M. M. Acharya, M. Sahoo and S. Acharya “Fuzzy linear programming problem with fuzzy decision variables : A geometrical approach”, Journal of Statistics and Management Systems, Vol 24, Issue 4, 2021.
[26] S. Gupta and A. Chug “Software maintainability prediction of open source datasets using least squares support vector machines”, Journal of Statistics and Management Systems, Vol 23, 2020.
[27] A. K. Dubey and V. Jain “Automatic facial recognition using VGG16 based transfer learning model” , Journal of Information and Optimization Sciences, volume 41, Issue 7, 2020.

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