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A Bayer motion estimation for motion-compensated frame interpolation

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Abstract

We propose a Bayer ME algorithm which is used to improve the performance of Motion-Compensated Frame Interpolation (MCFI). The core of the proposed algorithm is a predictive model designed from the alternate arrangement of Bayer pattern. According to the predictive model, the Motion Vector Field (MVF) of the interpolated frame is first split into basic blocks and absent blocks, and then an improved Bilateral Motion Estimation (BME) is proposed to compute the MVs of basic blocks. Finally, with the local stationary statistics of MVF, the MV of an absent block is predicted from the MVs of its neighboring basic blocks. Experimental results show that the proposed Bayer ME algorithm can improve both objective and subjective quality of the interpolated frame with a low computational complexity.

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References

  1. Alparone L, Barni M, Bartolini F, Cappellini V (1996) Adaptively weighted vector-median filters for motion fields smoothing. Proc IEEE Int Conf Acous Speech Sign Proc:2267–2270

  2. Chen WJ, Chang PY (2012) Effective demosaicking algorithm based on edge property for color filter arrays. Dig Sign Proc 22(1):163–169

    Article  MathSciNet  Google Scholar 

  3. Choi B-T, Lee S-H, Ko S-J (2000) New frame rate up-conversion using bi-directional motion estimation. IEEE Trans Consum Electron 46(3):603–609

    Article  Google Scholar 

  4. Choi BD, Han JW, Kim CS, Ko SJ (2007) Motion-compensated frame interpolation using bilateral motion estimation and adaptive overlapped block motion compensation. IEEE Trans Circ Syst Video Technol 17(4):407–416

    Article  Google Scholar 

  5. Dar Y, Bruckstein AM (2015) Motion-compensated coding and frame rate up-conversion: models and analysis. IEEE Trans Image Process 24(7):2051–2066

    MathSciNet  MATH  Google Scholar 

  6. Dikbas S, Altunbasak Y (2013) Novel true-motion estimation algorithm and its application to motion-compensated temporal frame interpolation. IEEE Trans Image Process 22(8):2931–2945

    Article  MathSciNet  MATH  Google Scholar 

  7. Gao X, Duanmu CJ, Zou C (2000) A multilevel successive elimination algorithm for block matching motion estimation. IEEE Trans Image Process 9(3):501–504

    Article  Google Scholar 

  8. Guo D, Lu Z (2016) Motion-compensated frame interpolation with weighted motion estimation and hierarchical vector refinement. Neurocomputing 181:76–85

    Article  Google Scholar 

  9. Haan GD, Biezen PWAC, Huijgen H, Ojo OA (1993) True motion estimation with 3-D recursive search block matching. IEEE Trans Circ Syst Video Technol 3(5):368–379

    Article  Google Scholar 

  10. Horé A, Ziou D (2011) An edge-sensing generic demosaicing algorithm with application to image resampling. IEEE Trans Image Process 20(11):3136–3150

    Article  MathSciNet  MATH  Google Scholar 

  11. Y. Huang, F. Chen, and S. Chien, “Algorithm and architecture design of multi-rate frame rate up-conversion for ultra-HD LCD systems,” IEEE Trans Circ Syst Video Technol, reprinted

  12. Jeon B-W, Lee G-I, Lee S-H, Park R-H (2003) Coarse-to-fine frame interpolation for frame rate up-conversion using pyramid structure. IEEE Trans Consum Electron 49(3):499–508

    Article  Google Scholar 

  13. Kang SJ, Cho KR, Kim YH (2007) Motion compensated frame rate up-conversion using extended bilateral motion estimation. IEEE Trans Consum Electron 53(4):1759–1767

    Article  Google Scholar 

  14. Kaviani HR, Shirani S (2016) Frame rate up-conversion using optical flow and patch-based reconstruction. IEEE Trans Circ Syst Video Technol 26(9):1581–1594

    Article  Google Scholar 

  15. Kim DY, Lim H, Park HW (2013) Iterative true motion estimation for motion-compensated frame interpolation. IEEE Trans Circ Syst Video Technol 23(3):445–454

    Article  Google Scholar 

  16. Li W, Salari E (1995) Successive elimination algorithm for motion estimation. IEEE Trans Image Process 4:105–107

    Article  Google Scholar 

  17. Lin YC, Tai SC (2002) Fast full-search block-matching algorithm for motion-compensated video compression. IEEE Trans Commun 45(5):527–531

    Google Scholar 

  18. Lu Q, Xu N, Fang X (2016) Motion-compensated frame interpolation with multiframe-based occlusion handling. J Disp Technol 12(1):45–54

    Article  Google Scholar 

  19. Orchard MT, Sullivan GJ (1994) Overlapped block motion compensation: an estimation-theoretic approach. IEEE Trans Image Process 3(5):693–699

    Article  Google Scholar 

  20. Pan Z, Lei J, Zhang Y, Sun X, Kwong S (2016) Fast motion estimation based on content property for low-complexity H.265/HEVC encoder. IEEE Trans Broadcast 62(3):675–684

    Article  Google Scholar 

  21. Subjective Video Quality Assessment Methods for Multimedia Applications (1999) Int. Telecommun. Union, Geneva, Switzerland

  22. Tsai TH, Lin HY (2012) High visual quality particle based frame rate up conversion with acceleration assisted motion trajectory calibration. J Disp Technol 8(6):341–351

    Article  Google Scholar 

  23. Tsai T, Shi A, Huang K (2016) Accurate frame rate up-conversion for advanced visual quality. IEEE Trans Broadcast 62(2):626–635

    Article  Google Scholar 

  24. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (Apr. 2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612

    Article  Google Scholar 

  25. Xia M, Yang G, Li L, Li R, Sun X (2017) Detecting video frame rate up-conversion based on frame-level analysis of average texture variation. Multimed Tools Appl 76(6):1–23

    Article  Google Scholar 

  26. Young DM, Gregory RT (1988) A survey of numerical mathematics. New York: Dover 2:759–762

    Google Scholar 

  27. Zhang Y, Zhao D, Liu H, Li Y, Ma S, Gao W (2012) Side information generation with auto regressive model for low-delay distributed video coding. J Vis Commun Image Represent 23(1):229–236

    Article  Google Scholar 

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China, under Grants nos. 61501393 and 61572417, in part by Nanhu Scholars Program for Young Scholars of XYNU, and in part by Innovation Team Support Plan of University Science and Technology of Henan Province (No. 19IRTSTHN014).

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  1. School of Computer and Information Technology, Xinyang Normal University, Xinyang, 464000, China

    Ran Li, Bingyu Ji, Yanling Li & Changan Wu

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  1. Ran Li
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  2. Bingyu Ji
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  3. Yanling Li
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  4. Changan Wu
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Correspondence to Ran Li.

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Li, R., Ji, B., Li, Y. et al. A Bayer motion estimation for motion-compensated frame interpolation. Multimed Tools Appl 78, 19603–19619 (2019). https://doi.org/10.1007/s11042-019-7337-6

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  • DOI: https://doi.org/10.1007/s11042-019-7337-6

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