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Computational Resource Management for Video Coding in Mobile Environments

  • Guilherme Correa
  • Pedro Assuncao
  • Luciano Agostini
  • Luis A. da Silva Cruz
Part of the Modeling and Optimization in Science and Technologies book series (MOST, volume 3)

Abstract

The increase of computational resources in mobile devices and the availability of reliable communication infrastructures provide support for acquisition, display, coding/decoding and transmission of high-resolution video in a broad set of equipment such as tablets and smartphones. Nevertheless, real-time video encoding and decoding is still a challenge in such computing environments, especially when considering the amount of computational resources required by state-of-the-art video coding standards. Moreover, battery technologies did not evolve as much as desired, which makes power consumption minimization an important issue for the mobile devices industry and users. Therefore, in current mobile systems, the available computational resources along with battery-life are responsible for imposing significant limitations on mobile real-time multimedia communications. This chapter presents an overview of the state-of-the-art research on management of computational resources for video encoding systems in mobile communications equipment. A review on computational complexity analysis of both H.264/AVC and HEVC video coding standards is presented, followed by a description of current methods for modelling, reducing and controlling the expenditure of computational resources on these video codecs. Finally, future trends on computational complexity management for video codecs implemented on power-constrained devices are lined out.

Keywords

Motion Estimation Video Code Mode Decision High Efficiency Video Code Video Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    International Telecommunication Union, ITU-T Recommendation H.264 (May 2003): advanced video coding for generic audiovisual services (2003)Google Scholar
  2. 2.
    ISO/IEC-JCT1/SC29/WG11, High Efficiency Video Coding (HEVC) text specification draft 10, Geneva, Switzerland (2013)Google Scholar
  3. 3.
    Zhihai, H., Yongfang, L., Lulin, C., Ahmad, I., Dapeng, W.: Power-rate-distortion analysis for wireless video communication under energy constraints. IEEE Transactions on Circuits and Systems for Video Technology 15, 645–658 (2005)CrossRefGoogle Scholar
  4. 4.
    Ates, H.F., Altunbasak, Y.: Rate-Distortion and Complexity Optimized Motion Estimation for H.264 Video Coding. IEEE Transactions on Circuits and Systems for Video Technology 18, 159–171 (2008)CrossRefGoogle Scholar
  5. 5.
    Wiegand, T., Sullivan, G.J., Bjontegaard, G., Luthra, A.: Overview of the H.264/AVC video coding standard. IEEE Transactions on Circuits and Systems for Video Technology 13, 560–576 (2003)CrossRefGoogle Scholar
  6. 6.
    ISO/IEC-JCT1/SC29/WG11, Comparison of Compression Performance of HEVC Working Draft 4 with AVC High Profile, Geneva, Switzerland (2011)Google Scholar
  7. 7.
    Sullivan, G.J., Wiegand, T.: Rate-distortion optimization for video compression. IEEE Signal Processing Magazine 15, 74–90 (1998)CrossRefGoogle Scholar
  8. 8.
    Ortega, A., Ramchandran, K.: Rate-distortion methods for image and video compression. IEEE Signal Processing Magazine 15, 23–50 (1998)CrossRefGoogle Scholar
  9. 9.
    Hallapuro, A., Lappalainen, V., Hamalainen, T.D.: Performance analysis of low bit rate H.26L video encoder. In: 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 2, pp. 1129–1132 (2001)Google Scholar
  10. 10.
    Saponara, S., Denolf, K., Lafruit, G., Blanch, C., Bormans, J.: Performance and Complexity Co-evaluation of the Advanced Video Coding Standard for Cost-Effective Multimedia Communications. EURASIP Journal on Applied Signal Processing 2004, 220–235 (2004)CrossRefGoogle Scholar
  11. 11.
    Joint Collaborative Team on Video Coding (JCT-VC) (2013), http://www.itu.int/en/ITU-T/studygroups/com16/video/Pages/jctvc.aspx
  12. 12.
    Sullivan, G.J., Ohm, J., Woo-Jin, H., Wiegand, T.: Overview of the High Efficiency Video Coding (HEVC) Standard. IEEE Transactions on Circuits and Systems for Video Technology 22, 1649–1668 (2012)CrossRefGoogle Scholar
  13. 13.
    Marpe, D., Schwarz, H., Bosse, S., Bross, B., Helle, P., Hinz, T., et al.: Video Compression Using Nested Quadtree Structures, Leaf Merging, and Improved Techniques for Motion Representation and Entropy Coding. IEEE Transactions on Circuits and Systems for Video Technology 20, 1676–1687 (2010)CrossRefGoogle Scholar
  14. 14.
    Laroche, G., Jung, J., Pesquet-Popescu, B.: RD Optimized Coding for Motion Vector Predictor Selection. IEEE Transactions on Circuits and Systems for Video Technology 18, 1681–1691 (2008)CrossRefGoogle Scholar
  15. 15.
    Helle, P., Oudin, S., Bross, B., Marpe, D., Bici, M.O., Ugur, K., et al.: Block Merging for Quadtree-Based Partitioning in HEVC. IEEE Transactions on Circuits and Systems for Video Technology 22, 1720–1731 (2012)CrossRefGoogle Scholar
  16. 16.
    Sole, J., Joshi, R., Nguyen, N., Tianying, J., Karczewicz, M., Clare, G., et al.: Transform Coefficient Coding in HEVC. IEEE Transactions on Circuits and Systems for Video Technology 22, 1765–1777 (2012)CrossRefGoogle Scholar
  17. 17.
    Sze, V., Budagavi, M.: High Throughput CABAC Entropy Coding in HEVC. IEEE Transactions on Circuits and Systems for Video Technology 22, 1778–1791 (2012)CrossRefGoogle Scholar
  18. 18.
    Sze, V., Budagavi, M.: Parallelization of CABAC transform coefficient coding for HEVC. In: 2012 Picture Coding Symposium, pp. 509–512 (2012)Google Scholar
  19. 19.
    Norkin, A., Bjontegaard, G., Fuldseth, A., Narroschke, M., Ikeda, M., Andersson, K., et al.: HEVC Deblocking Filter. IEEE Transactions on Circuits and Systems for Video Technology 22, 1746–1754 (2012)CrossRefGoogle Scholar
  20. 20.
    Chih-Ming, F., Alshina, E., Alshin, A., Yu-Wen, H., Ching-Yeh, C., Chia-Yang, T., et al.: Sample Adaptive Offset in the HEVC Standard. IEEE Transactions on Circuits and Systems for Video Technology 22, 1755–1764 (2012)CrossRefGoogle Scholar
  21. 21.
    Correa, G., Assuncao, P., Agostini, L., da Silva Cruz, L.A.: Performance and Computational Complexity Assessment of High Efficiency Video Encoders. IEEE Transactions on Circuits and Systems for Video Technology 22, 1899–1909 (2012)CrossRefGoogle Scholar
  22. 22.
    VTuneTM Amplifier XE 2011 from Intel (2013), http://software.intel.com/en-us/intel-vtune-amplifier-xe
  23. 23.
    Correa, G., Assuncao, P., Agostini, L., da Silva Cruz, L.A.: Complexity Control of High Efficiency Video Encoders for Power-Constrained Devices. IEEE Transactions on Consumer Electronics 57, 1866–1874 (2011)CrossRefGoogle Scholar
  24. 24.
    Bossen, F., Bross, B., Suhring, K., Flynn, D.: HEVC Complexity and Implementation Analysis. IEEE Transactions on Circuits and Systems for Video Technology 22, 1685–1696 (2012)CrossRefGoogle Scholar
  25. 25.
    Mattavelli, M., Brunetton, S.: Implementing real-time video decoding on multimedia processors by complexity prediction techniques. IEEE Transactions on Consumer Electronics 44, 760–767 (1998)CrossRefGoogle Scholar
  26. 26.
    Valentim, J., Nunes, P., Pereira, F.: Evaluating MPEG-4 video decoding complexity for an alternative video complexity verifier model. IEEE Transactions on Circuits and Systems for Video Technology 12, 1034–1044 (2002)CrossRefGoogle Scholar
  27. 27.
    van der Schaar, M., Andreopoulos, Y.: Rate-distortion-complexity modeling for network and receiver aware adaptation. IEEE Transactions on Multimedia 7, 471–479 (2005)CrossRefGoogle Scholar
  28. 28.
    Wang, Y., Shih-Fu, C.: Complexity Adaptive H.264 Encoding for Light Weight Streams. In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, p. II (2006)Google Scholar
  29. 29.
    Szu-Wei, L., Kuo, C.C.J.: Motion Compensation Complexity Model for Decoder-Friendly H.264 System Design. In: 2007 IEEE Workshop on Multimedia Signal Processing, pp. 119–122 (2007)Google Scholar
  30. 30.
    Rhee, C.E., Jung, J.S., Lee, H.J.: A Real-Time H.264/AVC Encoder With Complexity-Aware Time Allocation. IEEE Transactions on Circuits and Systems for Video Technology 20, 1848–1862 (2010)CrossRefGoogle Scholar
  31. 31.
    Kim, W., You, J., Jeong, J.: Complexity control strategy for real-time H.264/AVC encoder. IEEE Transactions on Consumer Electronics 56, 1137–1143 (2010)CrossRefGoogle Scholar
  32. 32.
    Xiang, L., Wien, M., Ohm, J.R.: Rate-Complexity-Distortion Optimization for Hybrid Video Coding. IEEE Transactions on Circuits and Systems for Video Technology 21, 957–970 (2011)CrossRefGoogle Scholar
  33. 33.
    Zhan, M., Hao, H., Yao, W.: On Complexity Modeling of H.264/AVC Video Decoding and Its Application for Energy Efficient Decoding. IEEE Transactions on Multimedia 13, 1240–1255 (2011)CrossRefGoogle Scholar
  34. 34.
    Koga, T., Iinuma, K., Hirano, A., Iijima, Y., Ishiguro, T.: Motion compensated interframe coding for video conferencing. In: National Telecommunications Conference, pp. G5.3.1–G5.3.5 (1981)Google Scholar
  35. 35.
    Lurng-Kuo, L., Feig, E.: A block-based gradient descent search algorithm for block motion estimation in video coding. IEEE Transactions on Circuits and Systems for Video Technology 6, 419–422 (1996)CrossRefGoogle Scholar
  36. 36.
    Renxiang, L., Bing, Z., Liou, M.L.: A new three-step search algorithm for block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 4, 438–442 (1994)CrossRefGoogle Scholar
  37. 37.
    Jo Yew, T., Surendra, R., Ranganath, M., Kassim, A.A.: A novel unrestricted center-biased diamond search algorithm for block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 8, 369–377 (1998)CrossRefGoogle Scholar
  38. 38.
    Shan, Z., Kai-Kuang, M.: A new diamond search algorithm for fast block-matching motion estimation. IEEE Transactions on Image Processing 9, 287–290 (2000)CrossRefGoogle Scholar
  39. 39.
    Ce, Z., Xiao, L., Chau, L.P.: Hexagon-based search pattern for fast block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 12, 349–355 (2002)CrossRefGoogle Scholar
  40. 40.
    Richardson, I.E.: Video Codec Design: Developing Image and Video Compression Systems. John Wiley & Sons, Inc. (2002)Google Scholar
  41. 41.
    Xuan-Quang, B., Yap-Peng, T.: Adaptive dual-cross search algorithm for block-matching motion estimation. IEEE Transactions on Consumer Electronics 50, 766–775 (2004)CrossRefGoogle Scholar
  42. 42.
    Lin, Y.-L.S., Kao, C.-Y., Kuo, H.-C., Chen, J.-W.: VLSI Design for Video Coding: H.264/AVC Encoding from Standard Specification to Chip. Springer Publishing Company, Inc. (2010)Google Scholar
  43. 43.
    Eckart, S., Fogg, C.E.: ISO-IEC MPEG-2 software video codec. In: SPIE Conf. Visual Communications and Image Processing, pp. 100–109 (1995)Google Scholar
  44. 44.
    Chok-Kwan, C., Lai-Man, P.: Normalized partial distortion search algorithm for block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 10, 417–422 (2000)CrossRefGoogle Scholar
  45. 45.
    Lengwehasarit, K., Ortega, A.: Probabilistic partial-distance fast matching algorithms for motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 11, 139–152 (2001)CrossRefGoogle Scholar
  46. 46.
    Li, W., Salari, E.: Successive elimination algorithm for motion estimation. IEEE Transactions on Image Processing 4, 105–107 (1995)CrossRefGoogle Scholar
  47. 47.
    Moecke, M., Seara, R.: Sorting Rates in Video Encoding Process for Complexity Reduction. IEEE Transactions on Circuits and Systems for Video Technology 20, 88–101 (2010)CrossRefGoogle Scholar
  48. 48.
    Saponara, S., Casula, M., Rovati, F., Alfonso, D., Fanucci, L.: Dynamic control of motion estimation search parameters for low complex H.264 video coding. IEEE Transactions on Consumer Electronics 52, 232–239 (2006)CrossRefGoogle Scholar
  49. 49.
    Bystrom, M., Richardson, I., Zhao, Y.: Efficient mode selection for H.264 complexity reduction in a Bayesian framework. Signal Processing: Image Communication 23, 71–86 (2008)Google Scholar
  50. 50.
    Pan, L.-J., Yo-Sung, H.: A Fast Mode Decision Algorithm for H.264/AVC Intra Prediction. In: 2007 IEEE Workshop on Signal Processing Systems, pp. 704–709 (2007)Google Scholar
  51. 51.
    Chun-Hao, C., Jia-Wei, C., Hsiu-Cheng, C., Yao-Chang, Y., Jinn-Shyan, W., Jiun-In, G.: A Quality Scalable H.264/AVC Baseline Intra Encoder for High Definition Video Applicaitons. In: 2007 IEEE Workshop on Signal Processing Systems, pp. 521–526 (2007)Google Scholar
  52. 52.
    De-Wei, L., Chun-Wei, K., Chao-Chung, C., Yu-Kun, L., Tian-Sheuan, C.: A 61MHz 72K Gates 1280x720 30FPS H.264 Intra Encoder. In: 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 801–804 (2007)Google Scholar
  53. 53.
    An-Chao, T., Jhing-Fa, W., Jar-Ferr, Y., Wei-Guang, L.: Effective Subblock-Based and Pixel-Based Fast Direction Detections for H.264 Intra Prediction. IEEE Transactions on Circuits and Systems for Video Technology 18, 975–982 (2008)CrossRefGoogle Scholar
  54. 54.
    Yu-Ming, L., Yu-Ting, S., Yinyi, L.: SATD-Based Intra Mode Decision for H.264/AVC Video Coding. IEEE Transactions on Circuits and Systems for Video Technology 20, 463–469 (2010)CrossRefGoogle Scholar
  55. 55.
    Hyungjoon, K., Altunhasak, Y.: Low-complexity macroblock mode selection for H.264-AVC encoders. In: 2004 International Conference on Image Processing, vol. 2, pp. 765–768 (2004)Google Scholar
  56. 56.
    Wang, F., Fan, Y., Lan, Y., Liu, W.: Fast intra mode decision algorithm in H.264/AVC using characteristics of transformed coefficients. In: 2008 International Conference on Visual Information Engineering, pp. 245–249 (2008)Google Scholar
  57. 57.
    Yu-Ming, L., Jyun-De, W., Yinyi, L.: An improved SATD-based intra mode decision algorithm for H.264/AVC. In: 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1029–1032 (2009)Google Scholar
  58. 58.
    Correa, G., Diniz, C., Bampi, S., Palomino, D., Porto, R., Agostini, L.: Homogeneity and distortion-based intra mode decision architecture for H.264/AVC. In: 2010 IEEE International Conference on Electronics, Circuits, and Systems, pp. 591–594 (2010)Google Scholar
  59. 59.
    Correa, G., Palomino, D., Diniz, C., Agostini, L., Bampi, S.: SHBS: A heuristic for fast inter mode decision of H.264/AVC standard targeting VLSI design. In: 2011 IEEE International Conference on Multimedia and Expo, pp. 1–4 (2011)Google Scholar
  60. 60.
    Correa, G., Palomino, D., Diniz, C., Bampi, S., Agostini, L.: Low-Complexity Hierarchical Mode Decision Algorithms Targeting VLSI Architecture Design for the H. In: 264/AVC Video Encoder, vol. 20, pp. 1–20 (2012)Google Scholar
  61. 61.
    Jeyun, L., Byeungwoo, J.: Fast mode decision for H.264. In: 2004 IEEE International Conference on Multimedia and Expo, vol. 2, pp. 1131–1134 (2004)Google Scholar
  62. 62.
    Wu, D., Pan, F., Lim, K.P., Wu, S., Li, Z.G., Lin, X., et al.: Fast intermode decision in H.264/AVC video coding. IEEE Transactions on Circuits and Systems for Video Technology 15, 953–958 (2005)CrossRefGoogle Scholar
  63. 63.
    Liquan, S., Zhi, L., Zhaoyang, Z., Xuli, S.: Fast Inter Mode Decision Using Spatial Property of Motion Field. IEEE Transactions on Multimedia 10, 1208–1214 (2008)CrossRefGoogle Scholar
  64. 64.
    Cho, S., Kim, M.: Fast CU Splitting and Pruning for Suboptimal CU Partitioning in HEVC Intra Coding. In: IEEE Transactions on Circuits and Systems for Video Technology (2013) (accepted for publication)Google Scholar
  65. 65.
    Bjontegaard, G.: Calculation of average PSNR differences between RD-curves, doc. VCEG-M33 (2001)Google Scholar
  66. 66.
    Tai, S.-C., Chang, C.-Y., Chen, B.-J., Hu, J.-F.: Speeding Up the Decisions of Quad-Tree Structures and Coding Modes for HEVC Coding Units. In: Pan, J.-S., Yang, C.-N., Lin, C.-C. (eds.) Advances in Intelligent Systems & Applications. SIST, vol. 21, pp. 393–401. Springer, Heidelberg (2012)Google Scholar
  67. 67.
    Xiaolin, S., Lu, Y., Jie, C.: Fast coding unit size selection for HEVC based on Bayesian decision rule. In: 2012 Picture Coding Symposium, pp. 453–456 (2012)Google Scholar
  68. 68.
    Zhang, Y., Wang, H., Li, Z.: Fast Coding Unit Depth Decision Algorithm for Interframe Coding in HEVC. In: 2013 Data Compression Conference, vol. 1, pp. 53–62 (2013)Google Scholar
  69. 69.
    Jie, L., Lei, S., Ikenaga, T., Sakaida, S.: Content Based Hierarchical Fast Coding Unit Decision Algorithm for HEVC. In: 2011 International Conference on Mutimedia and Signal Processing, vol. 1, pp. 56–59 (2011)Google Scholar
  70. 70.
    Sampaio, F., Bampi, S., Grellert, M., Agostini, L., Mattos, J.: Motion Vectors Merging: Low Complexity Prediction Unit Decision Heuristic for the Inter-prediction of HEVC Encoders. In: 2012 IEEE International Conference on Multimedia and Expo, pp. 657–662 (2012)Google Scholar
  71. 71.
    Guifen, T., Goto, S.: Content adaptive prediction unit size decision algorithm for HEVC intra coding. In: 2012 Picture Coding Symposium, pp. 405–408 (2012)Google Scholar
  72. 72.
    Kiho, C., Jang, E.S.: Early TU decision method for fast video encoding in high efficiency video coding. Electronics Letters 48, 689–691 (2012)CrossRefGoogle Scholar
  73. 73.
    Jaehwan, K., Jungyoup, Y., Kwanghyun, W., Byeungwoo, J.: Early determination of mode decision for HEVC. In: 2012 Picture Coding Symposium, pp. 449–452 (2012)Google Scholar
  74. 74.
    Cassa, M.B., Naccari, M., Pereira, F.: Fast rate distortion optimization for the emerging HEVC standard. In: 2012 Picture Coding Symposium, pp. 493–496 (2012)Google Scholar
  75. 75.
    Ma, S., Wang, S., Wang, S., Zhao, L., Yu, Q., Gao, W.: Low Complexity Rate Distortion Optimization for HEVC. In: 2013 Data Compression Conference, Snowbird, Utah, vol. 1, pp. 73–82 (2013)Google Scholar
  76. 76.
    Jain, P., Laffely, A., Burleson, W., Tessier, R., Goeckel, D.: Dynamically Parameterized Algorithms and Architectures to Exploit Signal Variations. The Journal of VLSI Signal Processing 36, 27–40 (2004)CrossRefGoogle Scholar
  77. 77.
    Weiyao, L., Panusopone, K., Baylon, D.M., Ming-Ting, S.: A Computation Control Motion Estimation Method for Complexity-Scalable Video Coding. IEEE Transactions on Circuits and Systems for Video Technology 20, 1533–1543 (2010)CrossRefGoogle Scholar
  78. 78.
    Akyol, E., Mukherjee, D., Yuxin, L.: Complexity Control for Real-Time Video Coding. In: 2007 IEEE International Conference on Image Processing, vol. 1, pp. 77–80 (2007)Google Scholar
  79. 79.
    da Fonseca, T.A., de Queiroz, R.L.: Macroblock sampling and mode ranking for complexity scalability in mobile H.264 video coding. In: 2009 IEEE International Conference on Image Processing, pp. 3753–3756 (2009)Google Scholar
  80. 80.
    Li, S., Yan, L., Feng, W., Shipeng, L., Wen, G.: Complexity-Constrained H.264 Video Encoding. IEEE Transactions on Circuits and Systems for Video Technology 19, 477–490 (2009)CrossRefGoogle Scholar
  81. 81.
    Xiang, L., Wien, M., Ohm, J.R.: Medium-granularity computational complexity control for H.264/AVC. In: 2010 Picture Coding Symposium, pp. 214–217 (2010)Google Scholar
  82. 82.
    Kannangara, C.S., Richardson, I.E., Bystrom, M., Yafan, Z.: Complexity Control of H.264/AVC Based on Mode-Conditional Cost Probability Distributions. IEEE Transactions on Multimedia 11, 433–442 (2009)CrossRefGoogle Scholar
  83. 83.
    Li, X., Cui, Y., Xue, Y.: Towards an Automatic Parameter-Tuning Framework for Cost Optimization on Video Encoding Cloud. International Journal of Digital Multimedia Broadcasting (2012)Google Scholar
  84. 84.
    Vanam, R., Riskin, E., Ladner, R., Hemami, S.: Fast algorithms for designing nearly optimal lookup tables for complexity control of the H.264 encoder. In: Signal, Image and Video Processing, pp. 1–13 (2012)Google Scholar
  85. 85.
    Breiman, L.: Classification and regression trees. Chapman & Hall, New York (1984)zbMATHGoogle Scholar
  86. 86.
    Sun, Z., Xi, C., Zhihai, H.: Adaptive Critic Design for Energy Minimization of Portable Video Communication Devices. In: 2008 International Conference on Computer Communications and Networks, pp. 1–5 (2008)Google Scholar
  87. 87.
    Kannangara, C.S., Richardson, I.E., Miller, A.J.: Computational Complexity Management of a Real-Time H.264/AVC Encoder. IEEE Transactions on Circuits and Systems for Video Technology 18, 1191–1200 (2008)CrossRefGoogle Scholar
  88. 88.
    Ismaeil, I.R., Docef, A., Kossentini, F., Ward, R.K.: A computation-distortion optimized framework for efficient DCT-based video coding. IEEE Transactions on Multimedia 3, 298–310 (2001)CrossRefGoogle Scholar
  89. 89.
    Yongfang, L., Ahmad, I.: Power and Distortion Optimization for Pervasive Video Coding. IEEE Transactions on Circuits and Systems for Video Technology 19, 1436–1447 (2009)CrossRefGoogle Scholar
  90. 90.
    Zhihai, H., Wenye, C., Xi, C.: Energy Minimization of Portable Video Communication Devices Based on Power-Rate-Distortion Optimization. IEEE Transactions on Circuits and Systems for Video Technology 18, 596–608 (2008)CrossRefGoogle Scholar
  91. 91.
    Ji, W., Liu, J., Chen, M., Chen, Y.: Power-efficient video encoding on resource-limited systems: A game-theoretic approach. Future Gener. Comput. Syst. 28, 427–436 (2012)CrossRefGoogle Scholar
  92. 92.
    da Fonseca, T.A., de Queiroz, R.L.: Complexity-Constrained Rate-Distortion Optimization for H.264/AVC Video Coding. In: 2011 IEEE International Symposium on Circuits and Systems, pp. 2909–2912 (2011)Google Scholar
  93. 93.
    Correa, G., Assuncao, P., Da Silva Cruz, L.A., Agostini, L.: Adaptive coding tree for complexity control of high efficiency video encoders. In: 2012 Picture Coding Symposium, pp. 425–428 (2012)Google Scholar
  94. 94.
    Correa, G., Assuncao, P., Agostini, L., da Silva Cruz, L.A.: Motion compensated tree depth limitation for complexity control of HEVC encoding. In: 2012 IEEE International Conference on Image Processing, pp. 217–220 (2012)Google Scholar
  95. 95.
    Correa, G., Assuncao, P., Agostini, L., da Silva Cruz, L.A.: Coding Tree Depth Estimation for Complexity Reduction of HEVC In. In: 2013 Data Compression Conference, vol. 1, pp. 43–52 (2013)Google Scholar
  96. 96.
    Kiho, C., Jang, E.S.: Leveraging Parallel Computing in Modern Video Coding Standards. IEEE Multimedia 19, 7–11 (2012)Google Scholar
  97. 97.
    Ngai-Man, C., Xiaopeng, F., Au, O.C., Man-Cheung, K.: Video Coding on Multicore Graphics Processors. IEEE Signal Processing Magazine 27, 79–89 (2010)CrossRefGoogle Scholar
  98. 98.
    Szu-Wei, L., Kuo, C.C.J.: Complexity Modeling of Spatial and Temporal Compensations in H.264/AVC Decoding. IEEE Transactions on Circuits and Systems for Video Technology 20, 706–720 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Guilherme Correa
    • 1
  • Pedro Assuncao
    • 2
  • Luciano Agostini
    • 3
  • Luis A. da Silva Cruz
    • 1
  1. 1.Instituto de TelecomunicaçõesUniversity of CoimbraCoimbraPortugal
  2. 2.Instituto de TelecomunicaçõesPolytechnic Institute of LeiriaLeiriaPortugal
  3. 3.GACIFederal University of PelotasPelotasBrazil

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