Skip to main content
Log in

Exploitation of motion non-stationarity at the encoder and decoder of DVC: a review

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

An Erratum to this article was published on 07 September 2016

Abstract

As a coding scheme for videos, distributed video coding (DVC) requires the development of motion information. However, motion content is unstable. In this article, we review motion non-stationarity considerations at the DVC encoder and decoder. The encoder focuses on adaptive exploration of the changes of interframe spatial-temporal correlation as the criterion for coding mode selection, where the algorithms are described from two distinct layers of block layer and frame layer. The decoder joins the nonlinear motion information in the side information (SI) generation, to estimate a real motion trajectory and obtain an accurate SI. Decoder motion analysis involves approaches using high-order motion model, global motion model, and local motion model. We also concern about the combination of encoder and decoder in presence of motion non-stationarity algorithms. Finally, the prospects in this field are proposed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Aaron A, Zhang R, Girod B (2002) Wyner-Ziv coding of motion video. In: Conference record of the thirty-sixth asilomar conference on signals, systems and computers. Pacific Grove

  2. Aaron A, Rane S, Girod B (2004) Wyner-Ziv video coding with hash-based motion compensation at the receiver. In: IEEE international conference on image processing (ICIP’04)

  3. Aaron A, Rane S, Setton E et al (2004) Transform-domain Wyner-Ziv codec for video. In: SPIE visual communications and image processing. San Jose

  4. Abou-Elailah A, Dufaux F, Farah J et al (2012) Fusion of global and local side information using support vector machine in transform-domain DVC. In: 20th IEEE European signal processing conference (EUSIPCO). Bucharest

  5. Abou-Elailah A, Dufaux F, Farah J et al (2013) Fusion of global and local motion estimation for distributed video coding. IEEE Trans Circ Syst Video Technol 23(1):158–172. doi:10.1109/TCSVT.2012.2203211

    Article  Google Scholar 

  6. Abou-Elailah A, Dufaux F, Farah J et al (2015) Fusion of global and local motion estimation using foreground objects for distributed video coding. IEEE Trans Circ Syst Video Technol 25(6):973–987. doi:10.1109/TCSVT.2014.2358872

    Article  Google Scholar 

  7. Abou-Elailah A, Farah J, Cagnazzo M et al (2011) Improved side information generation for distributed video coding. In: 2011 3rd European workshop on visual information processing (EUVIP). Paris

  8. Akinola M, Dooley L, Wong P (2010) Wyner-Ziv side information generation using a higher order piecewise trajectory temporal interpolation algorithm. In: 2010 International conference on graphic and image processing (ICGIP 2010). Manila

  9. Akinola MO, Dooley LS, Wong PKC (2011) Improved side information generation using adaptive overlapped block motion compensation and higher-order interpolation. In: 18th IEEE International conference on systems, signals and image processing (IWSSIP). Sarajevo

  10. Akinola MO, Dooley LS, Wong KCP (2015) Improving distributed video coding side information by intelligently combining macro-blocks from multiple algorithms. In: 2nd IET International conference on intelligent signal processing (ISP 2015). London

  11. Artigas X, Torres L (2005) Iterative generation of motion-compensated side information for distributed video coding. In: IEEE international conference on image processing (ICIP 2005)

  12. Artigas X, Ascenso J, Dalai M et al (2007) The DISCOVER codec: architecture, techniques and evaluation. In: Picture coding symposium (PCS’07). Lisbon

  13. Ascenso J, Brites C, Pereira F (2005) Motion compensated refinement for low complexity pixel based distributed video coding. In: IEEE conference on advanced video and signal based surveillance (AVSS 2005)

  14. Ascenso J, Brites C, Pereira F (2005) Improving frame interpolation with spatial motion smoothing for pixel domain distributed video coding. In: 5th EURASIP conference on speech and image processing, multimedia communications and services. Smolenice

  15. Ascenso J, Brites C, Pereira F (2006) Content adaptive Wyner-Ziv video coding driven by motion activity. In: IEEE International conference on image processing. Atlanta

  16. Ascenso J, Brites C, Pereira F (2010) A flexible side information generation framework for distributed video coding. Multimed Tools Appl 48(3):381–409. doi:10.1007/s11042-009-0316-6

    Article  Google Scholar 

  17. Ascenso J, Brites C, Pereira F (2011) A denoising approach for iterative side information creation in distributed video coding. In: 18th IEEE international conference on image processing (ICIP). Brussels

  18. Badem MB, Fernando WAC, Martinez JL et al (2009) An iterative side information refinement technique for transform domain distributed video coding. In: IEEE International conference on multimedia and expo (ICME 2009). New York

  19. Bernardini R, Rinaldo R, Zontone P et al (2006) Wavelet domain distributed coding for video. IL: IEEE International conference on image processing. Atlanta

  20. Bernardini R, Rinaldo R, Vitali A et al (2011) Performance evaluation of wavelet-based distributed video coding schemes. Signal Image Video Process 5 (1):49–60. doi:10.1007/s11760-009-0141-4

    Article  Google Scholar 

  21. Bjontegaard G (2001) Calcuation of average PSNR differences between RD-curves. Doc. VCEG-M33 ITU-T Q6/16. Austin

  22. Brites C, Ascenso J, Pereira F (2006) Improving transform domain Wyner-Ziv video coding performance. In: IEEE International conference on acoustics, speech and signal processing (ICASSP). Toulouse

  23. Brites C, Pereira F (2008) Correlation noise modeling for efficient pixel and transform domain Wyner-Ziv video coding. IEEE Trans Circ Syst Video Technol 18 (9):1177–1190. doi:10.1109/TCSVT.2008.924107

    Article  Google Scholar 

  24. Brites C, Pereira F (2015) Multiview side information creation for efficient Wyner-Ziv video coding: classifying and reviewing. Signal Process Image Commun 30:1–36. doi:10.1016/j.image.2014.11.001

    Article  Google Scholar 

  25. Brites C, Ascenso J, Pereira F (2013) Side information creation for efficient Wyner-Ziv video coding: classifying and reviewing. Signal Process Image Commun 28 (7):689–726. doi:10.1016/j.image.2013.05.002

    Article  Google Scholar 

  26. Cai S, Lin Z (2015) Advances in image and graphics technologies. Springer, Berlin Heidelberg, pp 167–175

    Book  Google Scholar 

  27. Cao Y, Gao S, Zhang C et al (2016) Towards practical distributed video coding for energy-constrained networks. Chin J Electron 25 (1):121–130. doi:10.1049/cje.2016.01.019

    Article  Google Scholar 

  28. Cheng S, Xiong Z (2005) Successive refinement for the Wyner-Ziv problem and layered code design. IEEE Trans Signal Process 53(8):3269–3281. doi:10.1109/TSP.2005.851138

    Article  MathSciNet  Google Scholar 

  29. Choi BD, Han JW, Kim CS et al (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. doi:10.1109/TCSVT.2007.893835

    Article  Google Scholar 

  30. Ciobanu L, Corte-Real L (2013) Multi-view codec with low-complexity encoding for distributed video coding. Multimed Tools Appl 64(3):731–755. doi:10.1007/s11042-011-0970-3

    Article  Google Scholar 

  31. Clerckx T, Munteanu A, Cornelis J et al (2007) Distributed video coding with shared encoder/decoder complexity. In: IEEE International conference on image processing (ICIP 2007). San Antonio

  32. Deligiannis N, Barbarien J, Jacobs M (2012) Side-information-dependent correlation channel estimation in hash-based distributed video coding. IEEE Trans Image Process 21(4):1934–1949. doi:10.1109/TIP.2011.2181400

    Article  MathSciNet  Google Scholar 

  33. Deligiannis N, Munteanu A, Wang S et al (2014) Maximum likelihood laplacian correlation channel estimation in layered wyner-ziv coding. IEEE Trans Signal Process 62(4):892–904. doi:10.1109/TSP.2013.2295556

    Article  MathSciNet  Google Scholar 

  34. Deligiannis N, Verbist F, Slowack J et al (2014) Progressively refined Wyner-Ziv video coding for visual sensors. ACM Trans Sensor Networks (TOSN) 10 (2):21. doi:10.1145/2530279

    Article  Google Scholar 

  35. Doulamis N, Doulamis A, Kalogeras D et al (1998) Low bit-rate coding of image sequences using adaptive regions of interest. IEEE Trans ACM Circ Syst Video Technol 8(8):928–934. doi:10.1109/76.736718

    Article  Google Scholar 

  36. Dufaux F, Ebrahimi T (2010) Encoder and decoder side global and local motion estimation for distributed video coding. In: IEEE International workshop on multimedia signal processing (MMSP). Saint Malo

  37. Esmaili GR (2011) Wyner-Ziv video coding: adaptive rate control. Key frame encoding and correlation noise classification. University of California, San Diego

  38. Esmaili GR, Cosman PC (2011) Wyner-Ziv video coding with classified correlation noise estimation and key frame coding mode selection 20(9):2463–2474. doi:10.1109/TIP.2011.2121079

  39. Girod B, Aaron A, Rane S et al (2005) Distributed video coding. Proc IEEE 93(1):71–83. doi:10.1109/JPROC.2004.839619

    Article  Google Scholar 

  40. Griessl M, Wittkop M, Wonneberger S (2005) Method and system for the estimation and compensation of brightness changes for optical flow calculations: U.S. Patent 6,959,118. 2005-10-25

  41. Guo C, Zhang L (2010) A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression 19(1):185–198. doi:10.1109/TIP.2009.2030969

  42. Guo X, Lu Y, Wu F et al (2008) Wyner-Ziv-based multiview video coding. IEEE Trans Circ Syst Video Technol 18(6):713–724. doi:10.1109/TCSVT.2008.920970

    Article  Google Scholar 

  43. Hansel R, Muller E (2011) Global motion guided adaptive temporal inter-/extrapolation for side information generation in distributed video coding. In: 18th IEEE International conference on image processing (ICIP). Brussels

  44. HoangVan X, Park J, Jeon B (2011) Flexible complexity control based on intra frame mode decision in distributed video coding. In: IEEE International symposium on broadband multimedia systems and broadcasting (BMSB). Nuremberg

  45. HoangVan X, Ascenso J, Pereira F (2014) Correlation modeling for a distributed scalable video codec based on the HEVC standard. In: 2014 IEEE 16th International workshop on multimedia signal processing (MMSP). Jakarta

  46. HoangVan X, Ascenso J, Pereira F (2014) Optimal reconstruction for a HEVC backward compatible distributed scalable video codec. In: 2014 IEEE Visual communications and image processing conference. Valletta

  47. HoangVan X, Ascenso J, Pereira F (2015) HEVC backward compatible scalability: a low encoding complexity distributed video coding based approach. Signal Process Image Commun 33:51–70. doi:10.1016/j.image.2015.02.003

    Article  Google Scholar 

  48. HoangVan X, Jeon B (2012) Flexible complexity control solution for transform domain Wyner-Ziv video coding. IEEE Trans Broadcast 58(2):209–220. doi:10.1109/TBC.2012.2187611

    Article  Google Scholar 

  49. Honn CK, Salleh MFM (2014) Performance evaluation of distributed video coding with different channel encoding techniques. In: 2014 IEEE International conference on computer and information sciences (ICCOINS). Kuala Lumpur

  50. Huo Y, Wang T, Maunder RG et al (2014) Motion-aware mesh-structured trellis for correlation modelling aided distributed multi-view video coding. IEEE Trans Image Process 23(1):319–331. doi:10.1109/TIP.2013.2288913

    Article  MathSciNet  Google Scholar 

  51. Huo Y, Wang T, Maunder RG et al (2014) Two-dimensional iterative source-channel decoding for distributed video coding. IEEE Commun Lett 18(1):90–93. doi:10.1109/LCOMM.2013.111513.132180

    Article  Google Scholar 

  52. Imran N, Seet BC, Fong ACM (2015) Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures. SpringerPlus 4 (1):1–30. doi:10.1186/s40064-015-1300-4

    Article  Google Scholar 

  53. Itti L (2004) Automatic foveation for video compression using a neurobiological model of visual attention. IEEE Trans Image Process 13(10):1304–1318. doi:10.1109/TIP.2004.834657

    Article  Google Scholar 

  54. ITU-T (1998) ITU-T Recommendation H.263 Version 2 (H.263+): video coding for low bitrate communication. ITU-T. Geneva

  55. Ji W, Frossard P, Chen Y (2014) EXIT-based side information refinement in Wyner-Ziv video coding. IEEE Trans Circ Syst Video Technol 24(1):141–156. doi:10.1109/TCSVT.2013.2276535

    Article  Google Scholar 

  56. Jia Y, Wang Y, Song R et al (2013) Decoder side information generation techniques in Wyner-Ziv video coding: a review. Multimed Tools Appl 74(6):1777–1803. doi:10.1007/s11042-013-1718-z

    Article  Google Scholar 

  57. Jung C, Jun D, Oh J et al (2010) Region-of-interest based pixel domain Wyner-Ziv coding. In: IEEE Military communications conference, 2010-Milcom 2010. San Jose, CA

  58. Kavitha S, Anandhi RJ (2015) A survey of image compression methods for low depth-of-field images and image sequences. Multimed Tools Appl 74(18):7943–7956. doi:10.1007/s11042-014-2032-0

    Article  Google Scholar 

  59. Kumar V, Sengupta S (2014) Side information refinement scheme in transform domain distributed video coding. In: 2014 IEEE Students’ technology symposium (TechSym). Kharagpur

  60. Kuo Y, Gao P, Chen J (2014) Distributed video coding with limited feedback requests. Multimed Tools Appl 4(75):2051–2065. doi:10.1007/s11042-014-2392-5

    Google Scholar 

  61. Lee JS, Ebrahimi T (2012) Perceptual video compression: a survey. IEEE J Selected Topics Signal Process 6(6):684–697. doi:10.1109/JSTSP.2012.2215006

    Article  Google Scholar 

  62. Lee MJ (2013) Distributed video coding with video analytics information for video surveillance application. Electron Lett 49(20):1265–1266. doi:10.1049/el.2013.1641

    Article  Google Scholar 

  63. Lee S, Park SJ (2013) Side information refinement for transform domain distributed video coding. Int J Multimed Ubiquitous Eng 8(5):1–10

    Article  Google Scholar 

  64. Li Y, Zhao D, Ma S et al (2009) Distributed video coding based on the human visual system. IEEE Signal Process Lett 16(11):985–988. doi:10.1109/LSP.2009.2028111

    Article  Google Scholar 

  65. Liu H, Ma S, Fan X et al (2010) Background aided surveillance-oriented distributed video coding. In: Picture coding symposium (PCS). Nagoya

  66. Micallef JJ, Farrugia RA, Debono CJ (2013) Modified distribution of correlation noise for improved Wyner-Ziv video coding performance. In: 2013 IEEE 15th International workshop on multimedia signal processing (MMSP). Pula

  67. Min K Y, Lim W, Nam J et al (2015) Distributed video coding supporting hierarchical GOP structures with transmitted EURASIP. J Image Video Process 2015 (1):1–14. doi:10.1186/s13640-015-0068-3

    Article  Google Scholar 

  68. Min K, Park S, Sim (2013) Distributed video coding based on adaptive slice size using received motion vectors. In: IEEE Picture coding symposium (PCS). Nagoya

  69. Min KY, Sim DG (2013) Adaptive distributed video coding with motion vectors through a back channel. EURASIP J Image Video Proces 2013(1):1–12. doi:10.1186/1687-5281-2013-22

    Article  Google Scholar 

  70. Ouaret M, Dufaux F, Ebrahimi T (2006) Fusion-based multiview distributed video coding. In: the 4th ACM international workshop on video surveillance and sensor networks (VSSN’06). Santa Barbara

  71. Park J, Jeon B (2016) Rate-constrained region of interest coding using adaptive quantization in transform domain Wyner-Ziv video coding. IEEE Trans Broadcast 99 (PP):1–15. doi:10.1109/TBC.2016.2515545

    Google Scholar 

  72. Pedro J, Soares L, Brites C et al (2007) Studying error resilience performance for a feedback channel based transform domain Wyner-Ziv video codec. In: Picture coding symposium (PCS’07). Lisbon

  73. Pereira F, Torres L, Guillemot C et al (2008) Distributed video coding: selecting the most promising application scenarios. Signal Process Image Commun 23 (5):339–352. doi:10.1016/j.image.2008.04.002

    Article  Google Scholar 

  74. Petrazzuoli G, Cagnazzo M, Pesquet-Popescu B (2010) High order motion interpolation for side information improvement in DVC. In: IEEE International conference on acoustics speech and signal processing (ICASSP). Dallas

  75. Petrazzuoli G, Cagnazzo M, Pesquet-Popescu B (2010) Fast and efficient side information generation in distributed video coding by using dense motion representation. In: 18th European signal processing conference (EUSIPCO-2010). Aalborg

  76. Petrazzuoli G, Cagnazzo M, Pesquet-Popescu B (2013) Novel solutions for side information generation and fusion in multiview DVC. EURASIP J Adv Signal Process 2013(1):1–17. doi:10.1186/1687-6180-2013-154

    Article  Google Scholar 

  77. Puri A, Eleftheriadis A (1998) MPEG-4: an object-based multimedia coding standard supporting mobile applications. Mobile Netw Appl 3(1):5–32. doi:10.1023/A:1019160312366

    Article  Google Scholar 

  78. Puri R, Ramchandran K (2002) PRISM: a video coding architecture based on distributed compression principles. In: 40th Allerton conference on communication, control, and computing. Allerton

  79. Puri R, Ramchandran K (2003) PRISM: a video coding architecture based on distributed compression principles. Tech. Rep. UCB/ERL M03/6. EECS Department, University of California, Berkeley

  80. Puri R, Majumdar A, Ramchandran K (2007) PRISM: a video coding paradigm with motion estimation at the decoder. IEEE Trans Image Process 16(10):2436–2448. doi:10.1109/TIP.2007.904949

    Article  MathSciNet  Google Scholar 

  81. Qing L, Zeng W (2014) Context-adaptive modeling for wavelet-domain distributed video coding. IEEE MultiMedia 21(4):84–93. doi:10.1109/MMUL.2014.48

    Article  Google Scholar 

  82. Salmistraro M, Ascenso J, Brites C et al (2014) A robust fusion method for multiview distributed video coding. EURASIP J Adv Signal Process 2014(1):1–16. doi:10.1186/1687-6180-2014-174

    Article  Google Scholar 

  83. Sehgal A, Jagmohan A, Ahuja N (2004) Wyner-Ziv coding of video: an error-resilient compression framework. IEEE Trans Multimed 6 (2):249–258. doi:10.1109/TMM.2003.822995

    Article  Google Scholar 

  84. Slepian D, Wolf JK (1973) Noiseless coding of correlated information sources. IEEE Trans Inf Theory 19(4):471–480. doi:10.1109/TIT.1973.1055037

    Article  MathSciNet  MATH  Google Scholar 

  85. Slowack J, Skorupa J, Mys S et al (2010) Flexible distribution of complexity by hybrid predictive-distributed video coding. Signal Process Image Commun 25 (2):94–110. doi:10.1016/j.image.2009.12.002

    Article  Google Scholar 

  86. Sofke S, Hansel R, Muller E (2009) Human visual system aware decoding strategies for distributed video coding. In: IEEE Picture coding symposium (PCS 2009). Chicago

  87. Sullivan GJ, Ohm J, Han WJ et al (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans Circ Syst Video Technol 22(12):1649–1668. doi:10.1109/TCSVT.2012.2221191

    Article  Google Scholar 

  88. Sun M, Wang Y, Yin H et al (2014) A novel layered DVC structure for wireless surveillance system. In: ACM Proceedings of international conference on internet multimedia computing and service. New York

  89. Sun YC, Tsai CJ (2012) Perceptual-based distributed video coding. J Vis Commun Image Represent 23(3):535–548. doi:10.1016/j.jvcir.2012.01.015

    Article  Google Scholar 

  90. Tagliasacchi M, Trapanese A, Tubaro S et al (2006) Intra mode decision based on spatio-temporal cues in pixel domain Wyner-Ziv video coding. In: IEEE International conference on acoustics, speech and signal processing (ICASSP 2006). Toulouse

  91. Taieb MH, Chouinard JY, Wang D (2013) Spatial correlation-based side information refinement for distributed video coding. EURASIP J Adv Signal Process 2013(1):1–19. doi:10.1186/1687-6180-2013-168

    Article  Google Scholar 

  92. Trapanese A, Tagliasacchi M, Tubaro S et al (2005) Embedding a block-based intra mode in frame-based pixel domain wyner-ziv video coding. In: Internationa Workshop on very low bitrate video coding. Costa del Rei

  93. Tsai D C, Lee C M, Lie W N (2007) Dynamic key block decision with spatio-temporal analysis for Wyner-Ziv video coding. In: IEEE International conference on image processing (ICIP 2007). San Antonio

  94. Verbist F, Deligiannis N, Chen W et al (2013) Transform-domain wyner-ziv video coding for 1k-pixel visual sensors. In: 2013 Seventh international conference on distributed smart cameras (ICDSC). Palm Springs

  95. Veselov A, Filippov B, Yastrebov V et al (2015) Intelligent interactive multimedia systems and services. Springer International Publishing, Switzerland, pp 179–189

    Google Scholar 

  96. Veselov A, Gilmutdinov MA Generalized correlation noise model for pixel domain Wyner-Ziv video coding. In: 2014 6th International congress on ultra modern telecommunications and control systems and workshops (ICUMT). St. Petersburg

  97. Vijayanagar K R, Kim J, Lee Y et al (2014) Low complexity distributed video coding. J Vis Commun Image Represent 25(2):361–372. doi:10.1016/j.jvcir.2013.12.006

    Article  Google Scholar 

  98. Wang Z, Lu L, Bovik AC (2003) Foveation scalable video coding with automatic fixation selection. IEEE Trans Image Process 12(2):243–254. doi:10.1109/TIP.2003.809015

    Article  Google Scholar 

  99. Wiegand T, Sullivan GJ, Bjontegaard G et al (2003) Overview of the H. 264/AVC video coding standard. IEEE Trans Circ Syst Video Technol 13(7):560–576. doi:10.1109/TCSVT.2003.815165

    Article  Google Scholar 

  100. Wu HF, Lee CH, Somayazulu VS et al (2014) Error resilience for key frames in distributed video coding with rate-distortion optimized mode decision. In: 2014 IEEE international symposium on circuits and systems (ISCAS). Melbourne

  101. Wyner AD, Ziv J (1976) The rate-distortion function for source coding with side information at the decoder. IEEE Trans Inf Theory 22(1):1–10. doi:10.1109/TIT.1976.1055508

    Article  MathSciNet  MATH  Google Scholar 

  102. Xiang W, Gao P, Peng Q (2015) Robust multiview three-dimensional video communications based on distributed video coding. IEEE Syst J 99(PP):1–11. doi:10.1109/JSYST.2015.2414662

    Article  Google Scholar 

  103. Xiaowen LIU, Shasha Y, Zhong Y (2014) Improvement of key frames in distributed video coding. Appl Res Comput 31 (2):619–624. doi:10.3969/j.issn.1001-3695.2014.02.073

    Google Scholar 

  104. Xu Q, Xiong Z (2006) Layered Wyner-Ziv video coding. IEEE Trans Image Process 15(12):3791–3803. doi:10.1109/TIP.2006.884925

    Article  MathSciNet  MATH  Google Scholar 

  105. Xu Q, Stankovic V, Xiong Z (2007) Wyner-Ziv video compression and fountain codes for receiver-driven layered multicast. IEEE Trans Circ Syst Video Technol 17 (7):901–906. doi:10.1109/TCSVT.2007.897464

    Article  Google Scholar 

  106. Yaacoub C, Farah J, Pesquet-Popescu B (2009) Content adaptive GOP size control with feedback channel suppression in distributed video coding. In: 16th IEEE International conference on image processing (ICIP). Cairo

  107. Yang HP, Ho MH, Hsieh HC et al (2015) Hardware implementation of a real-time distributed video decoder. In: 2015 IEEE International conference on digital signal processing (DSP). Singapore

  108. Yang XK, Ling WS, Lu Z K et al (2005) Just noticeable distortion model and its applications in video coding. Signal Process Image Commun 20(7):662–680. doi:10.1016/j.image.2005.04.001

    Article  Google Scholar 

  109. Yin M, Gao J, Shi D et al (2015) Band-level correlation noise modeling for Wyner-Ziv video coding with gaussian mixture models. Circ Syst Signal Process 34 (7):2237–2254. doi:10.1007/s00034-014-9951-x

    Article  MathSciNet  MATH  Google Scholar 

  110. Zhang D, Wu Y, Wan M (2014) Improved side information generation algorithm for Wyner-Ziv video coding. J Chin Univ Posts Telecommun 21(1):109–115. doi:10.1016/S1005-8885(14)60276-4

    Article  Google Scholar 

  111. Zhang L (2013) Research on key technology of video coding based on human visual system. Southwest Jiaotong University

  112. Zhang X, Liu J, Zhang B et al (2010) Adaptive key frame selection algorithm based on the interframe correlation in distributed video coding. J Optoelectronics Laser 21(10):1536–1541. doi:1005-0086(2010)10-1536-06

    Google Scholar 

  113. Zhao H, Yu X, Sun J et al (2008) An enhanced adaptive rood pattern search algorithm for fast block-matching motion estimation. In: IEEE Congress on image and signal processing (CISP’08). Sanya

  114. Zhao X, Liu J, Hu G et al (2013) Adaptive key-frame selection based on image features in distributed video coding. In: IEEE International conference on computational problem-solving (ICCP). Jiuzhai

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xin Zhao.

Additional information

This work has been supported by Beijing Municipal Natural Science Foundation (4152034).

An erratum to this article is available at http://dx.doi.org/10.1007/s11042-016-3887-z.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, X., Liu, J. & Hu, G. Exploitation of motion non-stationarity at the encoder and decoder of DVC: a review. Multimed Tools Appl 76, 13703–13738 (2017). https://doi.org/10.1007/s11042-016-3720-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3720-8

Keywords

Navigation