Skip to main content

Objective Hybrid Image Quality Metric for In-Service Quality Assessment

  • Chapter

Part of the book series: Multimedia Systems and Applications Series ((MMSA,volume 27))

Abstract

User-oriented image quality assessment has become a key factor in multimedia communications as a means of monitoring perceptual service quality. However, existing image quality metrics such as Peak Signal-to-Noise Ratio (PSNR) are inappropriate for in-service quality monitoring since they require the original image to be available at the receiver. Although PSNR and others are objective metrics, they are not based on human visual perception and are typically designed to measure the fidelity. On the other hand, the human visual system (HVS) is more sensitive to perceptual quality than fidelity. In order to overcome these problems, we propose a novel objective reduced-reference hybrid image quality metric (RR-HIQM) that accounts for the human visual perception and does not require a reference image at the receiver. This metric is based on the combination of several image artifact measures. The result is a single number, which represents overall image quality.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. V. Weerackody, C. Podilchuk, and A. Estrella, “Transmission of JPEG-Coded Images Over Wireless Channels,” Bell Laboratories Technical Journal, Autumn 1996.

    Google Scholar 

  2. M. Knee, “The Picture Appraisal Rating (PAR) — A Single-ended Picture Quality Measure for MPEG-2,” Technical Report, Snell and Wilcox, Jan. 2000.

    Google Scholar 

  3. A. Webster, “Objective and Subjective Evaluation for Telecommunications Services and Video Quality,” National Telecommunications and Information Administration (NTIA)/Institute for Telecommunication Science (ITS), Rapporteur Q21/9, 2002.

    Google Scholar 

  4. S. Winkler, “Vision Models and Quality Metrics for Image Processing Applications,” Ph.D. Thesis, École Polytechnique Fédéralé De Laussane (EPFL), Dec. 2000.

    Google Scholar 

  5. A. Jakulin, “Baseline JPEG and JPEG 2000 Artifacts Illustrated,” ‹http://ai.fri.unilj.si/~aleks/jpeg/artifacts.htm›, accessed on 8 May 2003.

    Google Scholar 

  6. S.D. Rane, J. Remus, and G. Sapiro, “Wavelet-Domain Reconstruction of Lost Blocks in Wireless Image Transmission and Packet-Switched Networks,” in Proc. of IEEE International Conference on Image Processing, pp. 309–312, 2002.

    Google Scholar 

  7. Z. Wang, A.C. Bovik, and B.L. Evans, “Blind Measurement of Blocking Artifacts in Images,” in Proc. of IEEE International Conference on Image Processing, pp. 981–984, Sep. 2000.

    Google Scholar 

  8. Z. Wang, H.R. Sheikh, and A.C. Bovik, “No-Reference Perceptual Quality Assessment of JPEG Compressed Images,” in Proc. of IEEE International Conference on Image Processing, pp. 477–480, Sep. 2002.

    Google Scholar 

  9. P. Marziliano, F. Dufaux, S. Winkler, and T. Ebrahimi, “A No-Reference Perceptual Blur Metric,” in Proc. of IEEE International Conference on Image Processing, pp. 57–60, Sep. 2002.

    Google Scholar 

  10. S. Saha and R. Vemuri, “An Analysis on the Effect of Image Activity on Lossy Coding Performance,” in Proc. of IEEE International Symposium on Circuits and Systems, pp. 295–298, May 2000.

    Google Scholar 

  11. T. M. Kusuma and H.-J. Zepernick, “In-Service Image Monitoring Using Perceptual Objective Quality Metrics,” Journal of Electrical Engineering, vol. 54, no. 9-10, pp. 237–243, Dec. 2003.

    Google Scholar 

  12. A.R. Weeks, “Fundamentals of Electronic Image Processing,” SPIE/IEEESeries on Imaging Science and Engineering, 1998.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer Science + Business Media, Inc.

About this chapter

Cite this chapter

Kusuma, T.M., Zepernick, HJ. (2005). Objective Hybrid Image Quality Metric for In-Service Quality Assessment. In: Wysocki, T.A., Honary, B., Wysocki, B.J. (eds) Signal Processing for Telecommunications and Multimedia. Multimedia Systems and Applications Series, vol 27. Springer, Boston, MA. https://doi.org/10.1007/0-387-22928-0_4

Download citation

  • DOI: https://doi.org/10.1007/0-387-22928-0_4

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-22847-1

  • Online ISBN: 978-0-387-22928-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics