Abstract
This paper proposes to simplify the motion estimation process of motion-compensated deinterlacing based on the results of scene change detection. The design idea consists of four parts: scene change detection, motion estimation, motion state analysis, and motion-compensated interpolation. First of all, scene change detection is performed in the current field and the backward field, followed by intra interpolation or motion-compensated interpolation based on backward, forward or bi-directional motion estimation. Compared with conventional motion estimation schemes, the motion estimation and motion-compensated interpolation processes are simplified for video sequences with frequent scene changes. Experimental results show that the proposed algorithm outperforms traditional ones in terms of objective and subjective qualities. Moreover, the additional complexity is marginal.
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References
De Haan, G., Bellers, E.B.: Deinterlacing–an overview. Proc. IEEE 86(9), 1839–1857 (1998)
Lin, S.F., Chang, Y.L., Chen, L.G.: Motion adaptive de-interlacing by horizontal motion detection and enhanced ELA processing. In: Proceedings of International Symposium on Circuits and Systems, Bangkok, Thailand, pp. II696–II699. IEEE (2003)
Kim, W., Jin, S., Jeong, J.: Novel intra deinterlacing algorithm using content adaptive interpolation. IEEE Trans. Consum. Electron. 53(3), 1036–1043 (2007)
Wang, A., Jeong, J.: Deinterlacing using multi direction detection with fixed adaptive tap interpolation filter. In: Proceedings of International Symposium on Broadband Multimedia Systems and Broadcasting, Seoul, Korea, pp. 1–5. IEEE (2012)
Gao, X., Gu, J., Li, J.: De-interlacing algorithms based on motion compensation. IEEE Trans. Consum. Electron. 51(2), 589–599 (2005)
Huang, Q., Gao, W., Zhao, D., Sun, H.: An efficient and robust adaptive deinterlacing technique. IEEE Trans. Consum. Electron. 52(3), 888–895 (2006)
Mohammadi, H.M., Langlois, P., Savaria, Y.: A five-field motion compensated deinterlacing method based on vertical motion. IEEE Trans. Consum. Electron. 53(3), 1117–1124 (2007)
Mahvash, H., Savaria, Y., Langlois, J.M.P.: Enhanced motion compensated deinterlacing algorithm. IET Image Proc. 6(8), 1041–1048 (2012)
Radwan, N.I., Salem, N.M., El Adawy, M.I.: Histogram correlation for video scene change detection. In: Wyld, D., Zizka, J., Nagamalai, D. (eds.) Advances in Computer Science, Engineering & Applications, vol. 166, pp. 765–773. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30157-5_76
Lin, C., Liaw, C.: A video de-interlacing with precise interfield information by hybrid scene change detection. In: Proceedings of International Conference on Telecommunications and Signal Processing, Rome, Italy, pp. 848–852. IEEE (2013)
Yi, X., Ling, N.: Fast pixel-based video scene change detection. In: Proceedings of International Symposium on Circuits and Systems, Kobe, Japan, pp. 3443–3446. IEEE (2005)
Wu, Z., Xu, P.: Shot boundary detection in video retrieval. In: Proceedings of International Conference on Electronics Information and Emergency Communication, Beijing, China, pp. 86–89. IEEE (2013)
Reddy, B., Jadhav, A.: Comparison of scene change detection algorithms for videos. In: Proceedings of International Conference on Advanced Computing and Communication Technologies, Rohtak, India, pp. 84–89. IEEE (2015)
De Haan, G., Biezen, P.W.A.C., Huijgen, H., et al.: True-motion estimation with 3-D recursive search block matching. IEEE Trans. Cir. Syst. Video Technol. 3(5), 368–379 (1993)
Huang, Q., Zhao, D., Ma, S., et al.: Deinterlacing using hierarchical motion analysis. IEEE Trans. Cir. Syst. Video Technol. 20(5), 673–686 (2010)
Zhang, H., Rong, M.: Deinterlacing algorithm using gradient-guided interpolation and weighted average of directional estimation. IET Image Proc. 9(6), 450–460 (2014)
Khan, S., Lee, D.: Efficient deinterlacing method using simple edge slope tracing. Opt. Eng. 54(10), 103–108 (2015)
Jang, S.M., Park, J.H., Hong, S.H.: Deinterlacing method based on edge direction refinement using weighted median filter. In: Proceedings of IEEE International Conference on Signal and Image Processing Applications, Kuala Lumpur, Malaysia, pp. 227–230. IEEE (2009)
Acknowledgments
This work is partly supported by the National Natural Science Foundation of China under Grant No. 61300122, 61502145 and 61602150, the National Key Technology Research and Development Program of the Ministry of Science and Technology of China under Grant No. 2016YFC0400910 and 2017ZX07104001, and the Fundamental Research Funds of China for the Central Universities under Grant No. 2013B01814.
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Zhu, X., Huang, Q., Ye, F., Liu, F., Xu, S., Wang, Y. (2018). Motion-Compensated Deinterlacing Based on Scene Change Detection. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_39
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DOI: https://doi.org/10.1007/978-3-319-77383-4_39
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