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Low-complexity motion estimation design using modified XOR function

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Abstract

Video coding techniques which are characterized by huge computational burden extensively consume power. Motion estimation with block matching criterion utilizing sum of absolute differences (SAD) with variable block size is the main source for such complexity and huge power consumption. In this work, we introduce a modified matching criterion in bit-level that lowers the computational complexity and hardware implementation when compared with the many SAD implementations introduced in the literature. We show that the number of hardware resources illustrated by the number of logic gates that are used in our design is much less than the number of the gates that are used in the traditional SAD and others in the literature. This leads in turn to a reduction in hardware complexity and consumed power. These are achieved by making our design rely on reusing the partial SAD values of smaller sub-blocks and then providing them to the compare and select unit as early as they are ready. Moreover, the final 41 motion vectors of motion estimation overlap in time and hence lower the number of output buses of the hardware implementation which results in a reduction in complexity as well. The video quality is only reduced by 0.17 dB while the bit-rate is increased only by 0.58 % in our simplified hardware architecture. The system logic synthesis is performed using the widely used FPGA platform. It produces 6.2 k LUT with a maximum operating frequency of 293 MHz (180 fps@CIF).

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References

  1. Al-Najdawi N, Al-Najdawi MN, Tedmori S (2014) Employing a novel cross-diamond search in a modified hierarchical search motion estimation algorithm for video compression. Inf Sci 268:425–435

    Article  MathSciNet  MATH  Google Scholar 

  2. Asano S, Shun ZZ, Maruyama T (2010) An FPGA implementation of full-search variable block size motion estimation. In: Field-Programmable Technology (FPT), 2010 International Conference on (pp. 399–402). IEEE

  3. Baek Y, Oh HS, Lee HK (1996) An efficient block-matching criterion for motion estimation and its VLSI implementation. IEEE Trans Consum Electron 42(4):885–892

    Article  Google Scholar 

  4. Bahari A, Arslan T, Erdogan AT (2007) Reduced computation and memory access for VBSME using pixel truncation. In: SOC Conference, 2007 I.E. International (pp. 59–62). IEEE

  5. Bahari A, Arslan T, Erdogan AT (2009) Low-power H. 264 video compression architectures for mobile communication. IEEE Trans Circ Syst Video Technol 19(9):1251–1261

    Article  Google Scholar 

  6. Bergmann HC (1982) Displacement estimation based on the correlation of image segments. In: Int. Conf. on Electronic Image Processing

  7. Celebi A, Lee HJ, Erturk S (2010) Bit plane matching based variable block size motion estimation method and its hardware architecture. IEEE Trans Consum Electron 56(3):1625–1633

    Article  Google Scholar 

  8. Celebi A, Urhan O, Hamzaoglu I, Erturk S (2009) Efficient hardware implementations of low bit depth motion estimation algorithms. IEEE Signal Process Lett 16(6):513–516

    Article  Google Scholar 

  9. Chatterjee SK, Chakrabarti I (2011) Power efficient motion estimation algorithm and architecture based on pixel truncation. IEEE Trans Consum Electron 57(4):1782–1790

    Article  Google Scholar 

  10. Chen CY, Chien SY, Huang YW, Chen TC, Wang TC, Chen LG (2006) Analysis and architecture design of variable block-size motion estimation for H. 264/AVC. IEEE Trans Circ Syst I Regular Papers 53(3):578–593

    Article  Google Scholar 

  11. Draft ITU-T Recommendation and Final Draft International Standard of Joint Video Specification H.264 (V9) (2014) (http://handle.itu.int/11.1002/1000/12063)

  12. Erturk S (2007) Multiplication-free one-bit transform for low-complexity block-based motion estimation. IEEE Signal Process Lett 14(2):109–112

    Article  Google Scholar 

  13. Erturk A, Erturk S (2005) Two-bit transform for binary block motion estimation. IEEE Trans Circ Syst Video Technol 15(7):938–946

    Article  Google Scholar 

  14. Feng J, Lo KT, Mehrpour H, Karbowiak AE (1995) Adaptive block matching motion estimation algorithm using bit-plane matching. In: Image processing, 1995. Proceedings, International Conference on (Vol. 3, pp. 496–499). IEEE

  15. Gu M, Yu N, Zhu L, Jia W (2011) High throughput and cost efficient VLSI architecture of integer motion estimation for H. 264/AVC. J Comput Inf Syst 7(4):1310–1318

    Google Scholar 

  16. Hameed R, Qadeer W, Wachs M, Azizi O, Solomatnikov A, Lee BC, Horowitz M (2010) Understanding sources of inefficiency in general-purpose chips. In: ACM SIGARCH Computer Architecture News (Vol. 38, No. 3, pp. 37–47). ACM

  17. Jain J, Jain A (1981) Displacement measurement and its application in interframe image coding. IEEE Trans Commun 29(12):1799–1808

    Article  Google Scholar 

  18. Joint Video Team (JVT) reference software version 10.2

  19. Kalaycioglu C, Ulusel OC, Hamzaoglu I (2009) Low power techniques for motion estimation hardware. In: Field Programmable Logic and Applications, 2009. FPL 2009. International Conference on (pp. 180–185). IEEE

  20. Le TM, Mason R, Panchanathan S (2000) Low complexity block motion estimation using morphological-based feature extraction and XOR operations. J Electron Imaging 9(2):110–116

    Article  Google Scholar 

  21. Lee S, Kim JM, Chae SI (1998) New motion estimation algorithm using adaptively quantized low bit-resolution image and its VLSI architecture for MPEG2 video encoding. IEEE Trans Circ Syst Video Technol 8(6):734–744

    Article  Google Scholar 

  22. Lee JH, Ra JB (2001) Efficient motion estimation using edge-based binary block-matching and refinement based on motion vector correlation. In: Image Processing, 2001. Proceedings. 2001 International Conference on (Vol. 2, pp. 957–960). IEEE

  23. Li BM, Leong PH (2008) Serial and parallel FPGA-based variable block size motion estimation processors. J Signal Process Syst 51(1):77–98

    Article  Google Scholar 

  24. Li R, Zeng B, Liou ML (1994) A new three-step search algorithm for block motion estimation. IEEE Trans Circ Syst Video Technol 4(4):438–442

    Article  Google Scholar 

  25. Luo JH, Wang CN, Chiang T (2002) A novel all-binary motion estimation (ABME) with optimized hardware architectures. IEEE Trans Circ Syst Video Technol 12(8):700–712

    Article  Google Scholar 

  26. Muralidhar P, Rao CR, Dwith CYN (2014) Efficient architecture for variable block size motion estimation in H. 264/AVC

  27. Natarajan B, Bhaskaran V, Konstantinides K (1997) Low-complexity block-based motion estimation via one-bit transforms. IEEE Trans Circ Syst Video Technol 7(4):702–706

    Article  Google Scholar 

  28. Ng KH, Po LM, Wong KM, Ting CW, Cheung KW (2009) Multiple block-size search algorithm for fast block motion estimation. In: Information, Communications and Signal Processing, 2009. ICICS 2009. 7th International Conference on (pp. 1–4). IEEE

  29. Olivares J, Hormigo J, Villalba J, Benavides I, Zapata EL (2006) SAD computation based on online arithmetic for motion estimation. Microprocess Microsyst 30(5):250–258

    Article  Google Scholar 

  30. Patras I, Hendriks EA, Lagendijk RL (2007) Probabilistic confidence measures for block matching motion estimation. IEEE Trans Circ Syst Video Technol 17(8):988–995

    Article  Google Scholar 

  31. Porto MS, Sanchez G, Noble D, Agostini L, Bampi S (2011) An efficient ME architecture for high definition videos using the new MPDS algorithm. In: Proceedings of the 24th symposium on Integrated circuits and systems design (pp. 119–124). ACM

  32. PowerPlay Early Power Estimator (EPE) and Power Analyzer. [online]. http://www.altera.com/support/devices/estimator/pow-powerplay.jsp

  33. Richmond RS, Ha DS (2001) A low-power motion estimation block for low bit-rate wireless video. In: Low Power Electronics and Design, International Symposium on, 2001. (pp. 60–63). IEEE

  34. Rong Y, Yu Q, An D, He Y (2013) Low power motion estimation based on non-uniform pixel truncation. In: Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific (pp. 1–4). IEEE

  35. Sampaio F, Zatt B, Shafique M, Agostini L, Bampi S, Henkel J (2013) Energy-efficient memory hierarchy for motion and disparity estimation in multiview video coding. In: Proceedings of the Conference on Design, Automation and Test in Europe (pp. 665–670). EDA Consortium

  36. Song X, Chiang T, Lee X, Zhang YQ (2000) New fast binary pyramid motion estimation for MPEG2 and HDTV encoding. IEEE Trans Circ Syst Video Technol 10(7):1015–1028

    Article  Google Scholar 

  37. Song CM, Guo Y, Wang XH, Liu D (2013) Fuzzy quantization based bit transform for low bit-resolution motion estimation. Signal Process Image Commun 28(10):1435–1447

    Article  Google Scholar 

  38. Tran TH, Cho HM, Cho SB (2009) Performance enhancement of sum of absolute difference (SAD) computation in H. 264/AVC using saturation arithmetic. In: Emerging intelligent computing technology and applications (pp. 396–404). Springer Berlin Heidelberg

  39. Vanne J, Aho E, Hamalainen TD, Kuusilinna K (2006) A high-performance sum of absolute difference implementation for motion estimation. IEEE Trans Circ Syst Video Technol 16(7):876–883

    Article  Google Scholar 

  40. Vanne J, Aho E, Kuusilinna K, Hamalainen TD (2009) A configurable motion estimation architecture for block-matching algorithms. IEEE Trans Circ Syst Video Technol 19(4):466–477

    Article  Google Scholar 

  41. Yeo H, Hu YH (1996) A novel architecture and processor-level design based on a new matching criterion for video compression. In: VLSI Signal Processing, IX, 1996, [Workshop on] (pp. 448–457). IEEE

  42. Zhu C, Lin X, Chau LP, Lim KP, Ang HA, Ong CY (2001) A novel hexagon-based search algorithm for fast block motion estimation. In: Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP’01). 2001 I.E. International Conference on (Vol. 3, pp. 1593–1596). IEEE

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Correspondence to Esam A. AlQaralleh.

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AlQaralleh, E.A., Abu-Sharkh, O.M.F. Low-complexity motion estimation design using modified XOR function. Multimed Tools Appl 75, 16809–16834 (2016). https://doi.org/10.1007/s11042-015-2948-z

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