Skip to main content
SpringerLink
Log in

RoDeRain: Rotational Video Derain via Nonconvex and Nonsmooth Optimization

  • Published:
Mobile Networks and Applications Aims and scope Submit manuscript

Abstract

Video derain is an important issue in the field of digital image processing and computer vision. This paper divides rain streaks into two types: one is rain in natural scenes, and the other is rain in stochastic scenes. In this paper, we propose a novel rotational video derain algorithm via nonconvex and nonsmooth algorithm (RoDerain). Not only can the rain streaks in natural scene be removed, but the rain streaks in stochastic scene can be also well removed. This paper added the rotation operator based on the discriminatively intrinsic priors of rain streaks and clean videos to remove the rain streaks in both natural and stochastic scenes.For the low rank problem of the background, we replace the solution of the nuclear norm with improved IRNN-Capped L1 suitable for tensor. Finally,this paper used the Alternating Direction Method of Multipliers (ADMM) to optimize the solution of the proposed rain streaks removal algorithm model.The disadvantage is that global information is not considered. And the extensive experiment results show that our proposed algorithm performs favorably in comparison to several popular rain removal algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Chang CC, Lin CJ (2012) Libsvm: a library for support vector machines. ACM Trans Intell Syst Technol 2(3):1–27

    Article  Google Scholar 

  2. Lu C, Tang J, Yan S et al (2014) Generalized nonconvex nonsmooth low-rank minimization. Western medicine; the medical journal of the west, 4130–4137

  3. Cai JF, Candas EJ, Shen ZA (2010) A singular value thresholding algorithm for matrix completion. SIAM J Optim 20(4):1956–1982

    Article  MathSciNet  Google Scholar 

  4. Chen YL, Hsu CT (2013) A generalized low-rank appearance model for spatio-temporally correlated rain streaks. In: Proceedings of the IEEE international conference on computer vision, pp 1968–1976

  5. Comaniciu D, Ramesh V, Meer P (2003) Kernel-based object tracking. IEEE Trans Pattern Anal Mach Intell 25:564–577

    Article  Google Scholar 

  6. Donoho DL (1995) De-noising by soft-thresholding. IEEE Trans Inf Theory 41(3):613–627

    Article  MathSciNet  Google Scholar 

  7. Ghadimi E, Teixeira A, Shames I et al (2015) Optimal parameter selection for the alternating direction method of multipliers (admm): quadratic problems. IEEE Trans Autom Control 60(3):644–658

    Article  MathSciNet  Google Scholar 

  8. Garg K, Nayar SK (2007) Vision and rain. Int J Comput Vis 75(1):3–27

    Article  Google Scholar 

  9. ALAA EAH (2014) A novel approach for rain removal from videos ssing low-rank recovery. In: Proceedings of 2014 fifth international conference on intelligent systems, modelling and simulation. IEEE Press, New York, pp 351–356

  10. KIM JH, SIM JY, KIM CS (2015) Video deraining and desnowing using temporal correlation and low-rank matrix completion. IEEE Trans Image Process 24(9):2658–2670

    Article  MathSciNet  Google Scholar 

  11. Alain H, Ziou D (2010) Image quality metrics: Psnr vs. ssim. In: 2010 International conference on pattern recognition. IEEE Computer Society

  12. Pan J, Su Z (1967) Fast l (0) -regularized kernel estimation for robust motion deblurring. Western medicine; the medical journal of the west 8(2):55

    Google Scholar 

  13. Jiang T, Huang T, Zhao X, Deng L, Wang Y (2019) Fastderain: a novel video rain streak removal method using directional gradient priors. IEEE Trans Image Process 28(4):2089–2102

    Article  MathSciNet  Google Scholar 

  14. Kang L-W, Lin C-W, Fu Y-H (2012) Automatic singleimage-based rain streaks removal via image decomposition. IEEE Trans Image Process 21(4):1742–1755

    Article  MathSciNet  Google Scholar 

  15. Chen YL, Hsu CT (2013) Proceedings of IEEE international conference on computer vision. IEEE Press, New York, pp 1968–1975. Geomatics and Information Science of Wuhan University

    Google Scholar 

  16. Zhang L, Zhang L, Mou X et al (2011) Fsim: a feature similarity index for image quality assessment. IEEE Trans Image Process 20(8):2378

    Article  MathSciNet  Google Scholar 

  17. Zhu L, Fu CW, Lischinski D et al (2017) Joint bi-layer optimization for single-image rain streak removal. In: 2017 IEEE International conference on computer vision (ICCV). IEEE Computer Society

  18. Li Y, Tan RT, Guo X, Lu J, Brown MS (2016) Rain streak removal using layer priors. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2736–2744

  19. Manu BN (2016) Rain removal from still images using l0 gradient minimization technique. In: International conference on information technology & electrical engineering. IEEE

  20. Srebro N, Jaakkola T (2003) Weighted low-rank approximations. In: Proceedings of 10th international conference on machine learning. American Association for Artificial Intelligence, Washington, p 2003

  21. Starik S, Werman M (2003) simulation of rain in videos texture workshop, vol 2. IEEE Press, Nice, pp 406–409

    Google Scholar 

  22. Okatani T, Yoshida T, Deguchi K (2011) Efficient algorithm for low-rank matrix factorization with missing components and performance comparison of latest algorithms. In: Proceedings of IEEE international conference on computer vision. IEEE Press, New York, pp 842–849

  23. Cao X (2006) Dynamic remote sensing monitoring of land use in nanjing based on tm images. Geomatics and Information Science of Wuhan University 31(11):958–961

    Google Scholar 

  24. Jiang T, Huang TZ, Zhao XL et al (2017) A novel tensor-based video rain streaks removal approach via utilizing discriminatively intrinsic priors. In: 30th IEEE Conference on computer vision and pattern recognition (CVPR 2017)

  25. Li Y, Tan RT, Guo X et al (2016) Rain streak removal using layer priors. Computer Vision and Pattern Recognition IEEE

  26. Weijiang Y, Huang Z, Zhang W, Feng L, Xiao N (2019) Gradual network for single image de-raining. In: Proceedings of the 27th ACM international conference on multimedia, pp 1795–1804

  27. Wang Z, Kang Q, Xun Y et al (2014) Military reconnaissance application of high-resolution optical satellite remote sensing. In: International symposium on optoelectronic technology & application: optical remote sensing technology & applications

  28. Zhu Z, Xu G, Yang B, Shi D, Lin X (2000) Visatram: a real-time vision system for automatic traffic monitoring. Image Vis Comput 18(10):781–794

    Article  Google Scholar 

  29. Zeng Y, Ma Z (2019) A lightweight channel-spatial attention network for real-time image de-raining. In: Proceedings of the 2019 2nd international conference on digital medicine and image processing. Association for Computing Machinery, pp 43–48

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant 61701259, 61572503, 61872424, 6193000388, and NUPTSF (Grant No. NY218001).

Author information

Authors and Affiliations

  1. National Engineering Research Center of Communication and Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, People’s Republic of China

    Lizhen Deng

  2. Department of Computer Science, Norwegian University of Science and Technology, 2815, Gjovik, Norway

    Guoxia Xu

  3. Jiangsu Province Key Lab on Image Processing and Image Communication, Nanjing University of Posts and Telecommunications, Nanjing, 210003, People’s Republic of China

    Hu Zhu

  4. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210003, People’s Republic of China

    Bing-Kun Bao

Authors
  1. Lizhen Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guoxia Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hu Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bing-Kun Bao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bing-Kun Bao.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deng, L., Xu, G., Zhu, H. et al. RoDeRain: Rotational Video Derain via Nonconvex and Nonsmooth Optimization. Mobile Netw Appl 26, 57–66 (2021). https://doi.org/10.1007/s11036-020-01721-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11036-020-01721-1

Keywords

Search

Navigation