Skip to main content

Advertisement

SpringerLink
Log in

The RR-PEVQ algorithm research based on active area detection for big data applications

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

Abstract

The reduced-reference video quality evaluation method uses only partial reference video information to evaluate the quality of deteriorated videos. This method can evaluate the quality of a video in real-time because less transmission bandwidth is required. Because the video active area attracts significant human eye attention, any deterioration in the active area will directly affect video evaluation results. Given the advantage of reduced reference model in VQM (Video Qualify Metric), this paper proposes a reduced reference evaluation model named RR-PEVQ (Reduced Reference Perceptual Evaluation of Video Quality) for weighting the active video area. According to the experimental results, the RR-PEVQ evaluation score is similar to that of the full reference PEVQ and the proposed method’s practicability is greatly improved for big data purposes.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Brunnstrom K, Hands D (2009, May) VQEG validation and ITU standardization of objective perceptual video quality metrices[J]. IEEE Signal Proc Mag [96]

  2. Bughin J, Chui M, Manyika J (2010) Clouds, big data, and smart assets: ten tech-enabled business trends to watch. McKinsey Quarterly 56(1):75–86

    Google Scholar 

  3. Chen W-M, Lai C-J, Wang H-C, Chao H-C, Lo C-H (2011) H.264 video watermarking with secret image sharing. IET Image Process 5(4):349–354

    Article  Google Scholar 

  4. Cheng R-S, Lin C-H, Chen J-L, Chao H-C (2012) Improving transmission quality of MPEG video stream by SCTP multi-streaming and differential RED. J Supercomput 62(1):68–83

    Article  Google Scholar 

  5. Feng C (2010) Image quality assessment-oriented frame capture of video phone over 3G system; Anti-counterfeiting, Security and Identification, p 359–362

  6. Gao X-B (2010) Quality assessment methods for visual information. XiDian University Publishing House, Xi’an

    Google Scholar 

  7. Hsu T-H, Liang Y-S (2011) Enabling adaptive video streaming for BitTorrent-like video systems. J Internet Technol 12(5):813–824

    Google Scholar 

  8. ITU-R Recommendation BT.500-11 (2002) Methodology for the subjective assessment of the quality of television pictures. International Telecommunication Union, Geneva, Switzerland

  9. ITU-T Recommendation J.244 (2008) Full reference and reduced reference calibration methods for video transmission systems with constant misalignment of spatial and temporal domains with constant gain and offset [S]

  10. ITU-T Recommendation J.247 (2008) Objective perceptual multimedia video quality measurement in the presence of a full reference. International Telecommunication Union, Geneva, Switzerland

  11. Ma G, Yang J, Zhou B (2008) Motion detection in video based on YUV color space [J]. Comput Eng Des 7.Vol 29

  12. Meng F, Jiang X, Sun H, Yang S (2007) Objective perceptual video quality measurement using a foveation-based reduced reference algorithm, 2007 I.E. International Conference on Multimedia and Expo, Beijing, China, July 2–5

  13. Pinson MH, Wolf S (2004) A new standardized method for objectively. IEEE Trans Broadcast 50(3):312–322

    Article  Google Scholar 

  14. Video material. [On line]. Available: http://vqa.como.polimi.it/

  15. Wu T-Y, Chen C-Y, Kuo L-S, Lee W-T, Chao H-C (2012) Cloud-based image processing system with priority-based data distribution mechanism. Comput Commun 35(15):1809–1818

    Article  Google Scholar 

  16. Zhou L, Chen M, Zhiwen Y, Rodrigues J, Chao H-C (2010) Cross-layer wireless video adaptation: tradeoff between distortion and delay. Comput Commun 33(14):1615–1622

    Article  Google Scholar 

Download references

Acknowledgments

The work presented in this paper was partially supported by 2011 National Natural Science Foundation of China (Grant number 61172097), 2012 Natural Science Foundation of Fujian (Grant number 2012J01424), NCETFJ, Fundamental Research Funds for the Central Universities (2012121028), and NSFC (61271242,61001072), Natural Science Foundation of Fujian Province of China (No.2010J01347), SRF for ROCS, SEM.

This research is supported by the Comba fund.

Author information

Authors and Affiliations

  1. School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China, 361005

    Wei-Jian Xu, Cai-Dan Zhao & Lianfen Huang

  2. School of Information and Engineering, Jimei University, Xiamen, Fujian, China, 361005

    Wei-Jian Xu

  3. Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan

    Hua-Pei Chiang & Yueh-Min Huang

Authors
  1. Wei-Jian Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cai-Dan Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hua-Pei Chiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lianfen Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yueh-Min Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cai-Dan Zhao.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xu, WJ., Zhao, CD., Chiang, HP. et al. The RR-PEVQ algorithm research based on active area detection for big data applications. Multimed Tools Appl 74, 3507–3520 (2015). https://doi.org/10.1007/s11042-014-1903-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-014-1903-8

Keywords

Search

Navigation