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Adaptive Spatio-Temporal Filtering with Motion Estimation for Mixed Noise Removal and Contrast Enhancement in Video Sequence

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Book cover Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 516))

Abstract

Naturally available noises in the videos are complex but fortunately they can be broadly classified as Gaussian and Impulse noises. Most of the available models for noise removal emphasize on any one kind of noise removal thus an optimum model of mixed noise removal is still a challenge. This paper describes about removal of video flickering and artifacts due to sensor motion, unprofessional recording behaviors, device defects, poor lighting conditions and high dynamic exposure. The adaptive spatio-temporal filter gives excellent result for mixed (Gaussian and Impulse) noise removal. Dense optical flow is introduced to reduce the motion blur and enhance the video. The analysis of PSNR and SSIM values were compared with existed method like Non-local Means and BM3D approach and results are tabulated. The Histogram graph gives the better intensity distribution in frames thus the proposed method even works good for low illumination or night vision surveillance videos.

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References

  1. P. Kisilev, S. Schein, Real-time video enhancement for high quality video conferencing. IEEE Trans. Commun. 31(4), 532–540 (2010)

    Google Scholar 

  2. R. Garnett, T. Huegerich, C. Chui, W. He, A universal noise removal algorithm with an impulse detector. IEEE Trans. Image Process. 14(11), 1747–1754 (2005)

    Article  Google Scholar 

  3. M. Szczepanski, Fast spatio-temporal digital paths video filter. Real-Time Image Process. (2016). doi:10.1007/s11554-016-0561-7. Springer, Berlin, Heidelberg

    Google Scholar 

  4. J. Astola, P. Haavisto, Y. Neuovo, Vector median filters. IEEE Proc. 78, 678–689 (1990)

    Article  Google Scholar 

  5. B. Smolka, Peer group switching filter for impulse noise reduction incolor images. Pattern Recogn. Lett. 31(6), 484–495 (2010). doi:10.1016/j.patrec.2009.09.012

    Article  Google Scholar 

  6. B. Smolka, K. Plataniotis, A. Chydzinski, M. Szczepanski, Self-adaptive algorithm of impulsive noise reduction in color images. Patt. Recogn. 35(8), 1771–1784 (2002)

    Article  MATH  Google Scholar 

  7. C. Tomasi, R. Manduchi, Bilateral filtering for gray and color images, in Proceedings of the 6th IEEE International Conference on Computer Vision (ICCV’98), Bombay, India, January 1998, pp. 839–846

    Google Scholar 

  8. M. Ben-Ezra, S. Nayar, Motion deblurring using hybrid imaging, in Proceedings of CVPR 2003 (2003), pp. I-657–664

    Google Scholar 

  9. P. Perona, J. Malik, Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12(7), 629–639 (1990)

    Article  Google Scholar 

  10. K. Buades Dabov, A. Foi, V. Katkovnik, K. Egiazarian, Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080–2095 (2007), doi:10.1109/TIP.2007.901238

  11. K. Radlak, B. Smolka, B, Trimmed non-local means technique for mixed noise removal in color images, in 2013 IEEE International Symposium on Multimedia (ISM) (2013), pp. 405–406

    Google Scholar 

  12. A. Buades, B. Coll, J.M. Morel, A non-local algorithm for image denoising, in Proceedings of CVPR 2005 (2005), pp. II-60–65

    Google Scholar 

  13. K. Dabov, A. Foi, V. Katkovnik, K. Egiazarian, Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080–2095 (2007), doi:10.1109/TIP.2007.901238

  14. M. Maggioni, V. Katkovnik, K. Egiazarian, A. Foi, Nonlocal transform-domain filter for volumetric data denoising and reconstruction. IEEE Trans. Image Process. 22(1), 119–133 (2013). doi:10.1109/TIP.2012.2210725

    Article  MathSciNet  Google Scholar 

  15. Y.W. Tai, H. Du, M. Brown, S. Lin, Image/video deblurring using a hybrid camera. Proc. CVPR 2008, 1–8 (2008)

    Google Scholar 

  16. C. Wang, L.-F. Sun, B. Yang, Y.-M. Liu, S-Q Yang, Video enhancement using adaptive spatio-temporal connective filter and piecewise mapping. EURASIP J. Adv. Signal Process. 13 pages (2008). Article ID 165792, doi:10.1155/2008/165792

  17. J. Portilla, V. Strela, M.J. Wainwright, E.P. Simoncelli, Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Trans. Image Process. 12(11), 1338–1351 (2003)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to S. Madhura .

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Madhura, S., Suresh, K. (2017). Adaptive Spatio-Temporal Filtering with Motion Estimation for Mixed Noise Removal and Contrast Enhancement in Video Sequence. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-10-3156-4_52

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  • DOI: https://doi.org/10.1007/978-981-10-3156-4_52

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