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An adaptive motion-compensated approach for video deinterlacing

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Abstract

Deinterlacing, defined as the process of converting a stream of interlaced frames into a sequence of progressive frames, represents a key feature in video processing. The interlaced video format, introduced by the old analog television transmission systems as a trade-off between framerate and bandwidth capacity, has become obsolete nowadays, when all transmissions are digital. Moreover, almost all recent displays—whether LCD or plasma—require progressive video input, whereas much of the available video content is in interlaced format. In this paper an adaptive, edge-preserving motion-compensated approach for video deinterlacing is proposed. The algorithm preserves strong edges and interpolates the missing pixels along the contours depending on the motion-degree of the region to which they belong. Our proposal is optimized to lower heavy computation, which is the main drawback of motion-compensated deinterlacing algorithms. Therefore it provides complexity scalability as a trade-off tool between performance and computation time. Experiments demonstrate a significant gain in reconstruction quality as compared to other deinterlacing implementations.

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References

  1. Bellers EB, Shuttent RJ, Kruetzmann M, Van der Heijden H, He H (2006) Directional and motion-compensated de-interlacing. In: Proceedings of the international conference on consumer electronics, pp 181–182

  2. Biswas M, Kumar S, Nguyen TQ (2006) Performance analysis of motion-compensated de-interlacing systems. IEEE Trans Image Process 15(9):2596–2609

    Article  Google Scholar 

  3. Brox P, Baturone I, Sanchez-Solano S (2009) Fuzzy motion-adaptive interpolation with picture repetition detection for deinterlacing. IEEE Trans Instrum Meas 58(9):2952–2958

    Article  Google Scholar 

  4. Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell PAMI-8(6):679–698

    Article  Google Scholar 

  5. Chang J, Kim YD, Shin GS, Kang MG (2009) Adaptive arbitration of intra-field and motion compensation methods for de-interlacing. IEEE Trans Circuits Syst Video Technol 19(8):1214–1220

    Article  Google Scholar 

  6. Chen YR, Tai SC (2009) True motion-compensated de-interlacing algorithm. IEEE Trans Circuits Syst Video Technol 19(10):1489–1498

    Article  Google Scholar 

  7. Chen T, Wu H, Yu ZH (2000) Efficient de-interlacing algorithm using edge-based line average interpolation. Opt Eng 39(8):2101–2105

    Article  Google Scholar 

  8. Chen M-J, Huang C-H, Hsu C-T (2004) Efficient de-interlacing technique by inter-field information. IEEE Trans Consum Electron 50(4):1202–1207

    Article  Google Scholar 

  9. Choi Y-J, Lim KW, Ra JB (2009) Improvement on optical flow based video deinterlacing by adopting flow vector and intensity reliabilities. In: 2009 16th IEEE international conference on image processing (ICIP), pp 393–396

  10. Dai S, Baker S, Kang SB (2009) An mrf-based deinterlacing algorithm with exemplar-based refinement. IEEE Trans Image Process 18(5):956–968

    Article  Google Scholar 

  11. De Haan G, Bellers EB (1997) De-interlacing of video data. IEEE Trans Consum Electron 43:819–825

    Article  Google Scholar 

  12. Doyle T, Looymans M (1989) Progressive scan conversion using edge information. In: Proc. of the 3rd international workshop on HDTV, pp 711–721

  13. Dubois E, de Haan G, Kurita T (1994) Motion estimation and compensation technologies for standards conversion. Signal Process Image Commun 6(3):189–190

    Article  Google Scholar 

  14. El-Qawasmeh E (2003) Scene change detection schemes for video indexing in uncompressed domain. Informatica 14:19–36

    MATH  Google Scholar 

  15. Engstorm EW (1935) A study of television image characteristics. Part II: Determination of frame frequency for television in terms of flicker characteristics. Proc IRE 23(4):295–310

    Article  Google Scholar 

  16. Fan Y-C, Chung C-H (2009) De-interlacing algorithm using spatial-temporal correlation-assisted motion estimation. IEEE Trans Circuits Syst Video Technol 19(7):932 –944

    Article  Google Scholar 

  17. Fan YC, Lin HS, Chiang A, Tsao HW, Kuo CC (2008) Motion compensated deinterlacing with efficient artifact detection for digital television displays. J. Display Technol 4(2):218–228

    Article  Google Scholar 

  18. Ghodstinat M, Bruhn A, Weickert J (2009) Deinterlacing with motion-compensated anisotropic diffusion. In: Cremers D, Rosenhahn B, Yuille A, Schmidt F (eds) Statistical and geometrical approaches to visual motion analysis, Lecture notes in computer science, vol 5064. Springer, Berlin, pp 91–106

    Chapter  Google Scholar 

  19. Haan GD, Bellers EB (1998) Deinterlacing - An overview. In:Proceedings of the IEEE 86(9):1839–1857

    Article  Google Scholar 

  20. Hong S-H, Park R-H, Yang S, Kim J-Y (2006) Edge-preserving spatial deinterlacing for still images using block-based region classification. Dept. of Electr. Eng., Sogang Univ., Seoul, South Korea

    Google Scholar 

  21. Huang Q, Gao W, Zhao D, Sun H (2006) An efficient and robust adaptive deinterlacing technique. IEEE Trans Consum Electron 52(3):888–895

    Article  Google Scholar 

  22. Huang Q, Zhao D, Ma S, Gao W, Sun H (2010) Deinterlacing using hierarchical motion analysis. IEEE Trans Circuits Syst Video Technol 20(5):673–686

    Article  Google Scholar 

  23. Jeon G, Anisetti M, Kim D, Bellandi V, Damiani E, Jeong J (2009) Fuzzy rough sets hybrid scheme for motion and scene complexity adaptive deinterlacing. Image Vis Comput 27(4):425–436

    Article  Google Scholar 

  24. Jeon G, You J, Jeong J (2009) Weighted fuzzy reasoning scheme for interlaced to progressive conversion. IEEE Trans Circuits Syst Video Technol 19(6):842 –855

    Article  Google Scholar 

  25. Ji G, Zhong Q (2010) A fast motion compensated deinterlacing method with true sub-pixel accurate motion vectors. In: 2010 IEEE 10th international conference on signal processing (ICSP), pp 771–774

  26. Kim W, Jin S, Jeong J (2007) Novel intra deinterlacing algorithm using content adaptive interpolation. IEEE Trans Consum Electron 53(3):1036–1043

    Article  Google Scholar 

  27. Kwon O, Sohn K, Lee C (2003) Deinterlacing using directional interpolation and motion compensation. IEEE Trans Consum Electron 49(1):198–203

    Article  Google Scholar 

  28. Lee K, Lee C (2010) High quality deinterlacing using content adaptive vertical temporal filtering. IEEE Trans Consum Electron 56(4):2469 –2474

    Article  Google Scholar 

  29. Lee GG, Wang M-J, Li H-T, Lin H-Y (2008) A motion-adaptive deinterlacer via hybrid motion detection and edge-pattern recognition. EURASIP J Image Video Process 2008:10

  30. Lee K, Lee J, Lee C (2009) Deinterlacing with motion adaptive vertical temporal filtering. IEEE Trans Consum Electron 55(2):636 –643

    Article  Google Scholar 

  31. Li M, Nguyen T (2007) A de-interlacing algorithm using markov random field model. IEEE Trans Image Process 16(11):2633–2648

    Article  MathSciNet  Google Scholar 

  32. Lin S-F, Chang Y-L, Chen L-G (2003) Motion adaptive interpolation with horizontal motion detection for deinterlacing. IEEE Trans Consum Electron 49(4):1256–1265

    Article  Google Scholar 

  33. Lin C-C, Sheu M-H, Chiang H-K, Wei C-J, Liaw C (2007) A high-performance architecture of motion adaptive de-interlacing with reliable interfield information. IEICE Trans Fundam Electron Commun Comput Sci 90(11):2575–2583

    Article  Google Scholar 

  34. Mohammadi HM, Langlois P, Savaria Y (2007) A five-field motion compensated deinterlacing method based on vertical motion. IEEE Trans Consum Electron 53(3):1117–1124

    Article  Google Scholar 

  35. Park MK, Kang MG, Nam K, Oh SG (2003) New edge dependent deinterlacing algorithm based on horizontal edge pattern. IEEE Trans Consum Electron 49(4):1508–1512

    Article  Google Scholar 

  36. Pigeon S, Vandendorpe L, Cuvelier L, Maison B (1995) Specification of a generic format converter. CEC RACE/HAMLET deliverable no R2110/WP2/DS/S/006/b1

  37. Spen Y, Zhang D, Zhang Y, Li J (2006) Motion adaptive deinterlacing of video data with texture detection. IEEE Trans Consum Electron 52(4):1403–1408

    Article  Google Scholar 

  38. Sze K-W, Lam K-M, Qiu G (2003) Scene cut detection using the colored pattern appearance model. Model, ICIP 2:1017–1020

    Google Scholar 

  39. Tu S-F, Au OC, Wu Y, Luo E, Yeung C-H (2009) A robust spatial-temporal line-warping based deinterlacing method. In:Proceedings of the 2009 IEEE international conference on multimedia and expo (ICME’09), pp 77–80

  40. Usama S, Montaser M, Ahmed O (2005) A complexity and quality evaluation of block based motion estimation algorithms. Czech J Adv Eng Acta Polytech 45(1):29–41

    Google Scholar 

  41. Wang D, Vincent A, Blanchfield P (2005) Hybrid de-interlacing algorithm based on motion vector reliability. IEEE Trans Circuits Syst Video Technol 15(8):1019–1025

    Article  Google Scholar 

  42. Yang S, Kim D, Jeong J (2009) Fine edge-preserving deinterlacing algorithm for progressive displays. IEEE Trans Consum Electron 55(3):1654–1662

    Article  Google Scholar 

  43. Yu L, Li J, Zhang Y, Shen Y (2006) Motion adaptive deinterlacing with accurate motion detection and anti-aliasing interpolation filter. IEEE Trans Consum Electron 52(2):712–717

    Article  Google Scholar 

  44. Zhanguzin D, Trocan M, Mikovicova B (2010) An edge-preserving motion-compensated approach for video deinterlacing. In: IEEE/IET/BCS 3rd international workshop on future multimedia networking

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Correspondence to Maria Trocan.

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Trocan, M., Mikovicova, B. & Zhanguzin, D. An adaptive motion-compensated approach for video deinterlacing. Multimed Tools Appl 61, 819–837 (2012). https://doi.org/10.1007/s11042-011-0845-7

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