Skip to main content

Abstract

What is implied by the statement that the subjective quality of a number of images has been measured? Especially in an engineering community, where (objective) measurement and (subjective) judgement are usually kept very separate, the above question may need some clarification. We will start by making more precise what is understood by measurement and subjective in the current context.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A. Agresti: “Categorical data analysis.” Psychological Bulletin 105: 290–301, 1989.

    Article  Google Scholar 

  2. A. Agresti: Categorical Data Analysis. John Wiley and Sons Inc.: New York, 1990.

    MATH  Google Scholar 

  3. J. Anderson, P. Philips: “Regression, discrimination and measurement models for ordered categorical variables.” Applied Statistics 30: 22–31, 1981.

    Article  MathSciNet  MATH  Google Scholar 

  4. N. Anderson: “Functional measurement and psychological judgment.” Psychological Review 77: 153–170, 1970.

    Article  Google Scholar 

  5. R. Atkinson et al. (eds.): Stevens’ Handbook of Experimental Psychology — Perception and Motivation. John Wiley and Sons Inc.: New York, 1988.

    Google Scholar 

  6. K. Boff, L. Kaufman, J. Thomas (eds.): Handbook of Perception and Human Performance — Sensory Processes and Perception. John Wiley and Sons Inc.: New York, 1986.

    Google Scholar 

  7. M. Boschman: “Difscal: A program for the analysis of difference scaling results (v2.1).” IPO-Institute for Perception Research Manual 145, 1997.

    Google Scholar 

  8. M. Boschman: “Thurcatd: A program for the analysis of ordinal category scaling results (v2.1).” IPO-Institute for Perception Research Manual 144, 1997.

    Google Scholar 

  9. M. Boschman: “Difscal: A tool for analysing difference ratings on an ordinal category scale.” Behavior Research Method, Instruments and Computers submitted, 2000.

    Google Scholar 

  10. M. Boschman: “Thurcatd: A tool for analyzing ratings on an ordinal category scale.” Behavior Research Method, Instruments and Computers 32: 379–388, 2000.

    Article  Google Scholar 

  11. H. de Ridder: “Current issues and new techniques in visual quality assessment.” in Proceedings of the IEEE International Conference on Image Processing, pp. 869–872, 1996.

    Chapter  Google Scholar 

  12. H. de Ridder, G. Majoor: “Numerical category scaling: An efficient method for assessing digital image coding impairments.” in Human Vision and Electronic Imaging: Models, Methods and Applications, eds. B. Rogowitz, J. Allebach, vol. 1249, pp. 65–77, Proceedings of the SPIE, 1990.

    Google Scholar 

  13. J. Falmagne: “Psychophysical measurement and theory.” in Boff et al. (6), pp. 1–66.

    Google Scholar 

  14. M. Freeman, J. Tukey: “Transformations related to the angular and the square root.” Annals of Mathematical Statistics 21: 607–611, 1950.

    Article  MathSciNet  MATH  Google Scholar 

  15. D. Gun et al.: “Forced choice and ordinal discrete rating assessment of image quality: A comparison.” Journal of Digital Imaging 10: 103–107, 1997.

    Google Scholar 

  16. ITU-R: “Methodology for the subjective assessment of the quality of television pictures.” Recommendation ITU-R BT.500–8 pp. 1–35, 1998.

    Google Scholar 

  17. J. Kruskal: “Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis.” Psychometrica 29: 1–27, 1964.

    Article  MathSciNet  MATH  Google Scholar 

  18. J. Kruskal: “Nonmetric multidimensional scaling: a numerical method.” Psychometrica 29: 115–129, 1964.

    Article  MathSciNet  MATH  Google Scholar 

  19. H. Levitt: “Transformed up-down methods in psychoacoustics.” Journal of the Acoustical Society of America 49: 467–476, 1971.

    Article  Google Scholar 

  20. R. Luce, C. Krumhansl: “Measurement, scaling, and psychophysics.” in Atkinson et al. (5), pp. 3–74.

    Google Scholar 

  21. J. Martens, G. Majoor: “The perceptual relevance of scale-space image coding.” Signal Processing 17: 353–364, 1989.

    Article  Google Scholar 

  22. F. Mosteller: “Remarks on the method of paired comparisons: Iii a test of significance for paired comparisons when equal standard deviations and equal correlations are assumed.” Psychometrika 16: 207–218, 1951.

    Article  Google Scholar 

  23. F. Mounts, A. Netravali, P. B.: “Design of quantizers for real-time hadamard-transform coding of pictures.” Bell System Technical Journal 56: 21–48, 1977.

    Google Scholar 

  24. A. Parducci, D. Wedell: “The category effect with rating scales: Number of categories, number of stimuli, and method of presentation.” Journal of Experimental Psychology: Human Perception and Performance 12: 496–516, 1986.

    Article  Google Scholar 

  25. J. Roufs, F. Blommaert, H. de Ridder: “Brightness-luminance relations: Future developments in the light of the past.” in Proceedings of the CIE, Melbourne, Australia, 1991.

    Google Scholar 

  26. R. Shepard: “The analysis of proximities: Multidimensional scaling with an unknown distance function.” Psychometrica 27: 219–246, 1962.

    Article  MathSciNet  Google Scholar 

  27. S. Stevens: “On the psychophysical law.” Psychological Review 64: 153–181, 1957.

    Article  Google Scholar 

  28. K. Teunissen: “The validity of ccir quality indicators along a graphical scale.” SMPTE Journal 105: 144–149, 1996.

    Article  Google Scholar 

  29. L. Thurstone: “A law of comparative judgement.” Psychological Review 34: 273–286, 1927.

    Article  Google Scholar 

  30. W. Torgerson: Theory and Methods of Scaling. John Wiley and Sons Inc.: New York, 1958.

    Google Scholar 

  31. H. van Trees: Detection, Estimation an Modulation Theory. John Wiley and Sons Inc.: New York, 1968.

    Google Scholar 

  32. W Wagenaar: “Stevens versus fechner: A plea for dismissal of the case.” Acta Psychologica 39: 225–235, 1975.

    Article  Google Scholar 

  33. T. Wickens: “Tutorial on modeling ordered categorical response data.” Annual Review of Psychology 48: 537–558, 1998.

    Article  Google Scholar 

  34. F. Young: “Scaling.” Annual Review of Psychology 35: 55–81, 1984.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Martens, JB., Boschman, M. (2001). The Psychophysical Measurement of Image Quality. In: van den Branden Lambrecht, C.J. (eds) Vision Models and Applications to Image and Video Processing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3411-9_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-4757-3411-9_5

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-4905-9

  • Online ISBN: 978-1-4757-3411-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics