Advertisement

Information-Theoretic Assessment

  • Friedrich O. Huck
  • Carl L. Fales
  • Zia-ur Rahman
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 409)

Abstract

This chapter introduces information theory into the mathematical development to establish an approach, based on fundamental principles, for the assessment of visual communication. In this assessment, we must clearly distinguish image reconstruction (Chapter 2) from restoration (Chapter 3). Whereas the reconstruction is intended to produce a continuous representation of the discrete output of the image-gathering device, the restoration is intended to produce a representation of the input to this device. The information-theoretic assessment is meaningful only for image restoration for which a close correlation evolves between information rate and image quality.

Keywords

Visual Quality Quantization Level Quantization Noise Image Restoration Information Rate 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    C. E. Shannon, “A mathematical theory of communication,” Bell Syst. Tech. J. 27, 379-423, and 28, 623-656 (1948); C. E. Shannon and W. Weaver, The Mathematical Theory of Communication (U. Illinois Press, Urbana, 1964 ).Google Scholar
  2. 2.
    P. B. Fellgett and E. H. Linfoot, “On the assessment of optical images,” Philos. Trans. Roy. Soc. London 247, 369 - 407 (1955).MathSciNetCrossRefGoogle Scholar
  3. 3.
    E. H. Linfoot, “Information theory and optical images,” J. Opt. Soc. Am. 45, 808 - 819 (1955).CrossRefGoogle Scholar
  4. 4.
    E. H. Linfoot, “Transmission factors and optical design,” J. Opt. Soc. Amer. 46, 740 - 752 (1956).MathSciNetCrossRefGoogle Scholar
  5. 5.
    E. H. Linfoot, “Quality evaluations of optical systems,” Optica Ada 5, 1 - 14 (1958).MATHCrossRefGoogle Scholar
  6. 6.
    B. R. Frieden, “Information, and the restorability of images,” J. Opt. Soc. Am. 60, 575 - 576 (1970).CrossRefGoogle Scholar
  7. 7.
    F. O. Huck, C. L. Fales, J. A. McCormick and S. K. Park, “Image-gathering system design for information and fidelity,” J. Opt. Soc. Am. A5, 285 - 299 (1988).CrossRefGoogle Scholar
  8. 8.
    C. E. Shannon, “Coding theorems for a discrete source with a fidelity criterion.” In: R. A. Machol, ed., Information and Decision Process (McGraw-Hill, New York, 93-126, 1960); IRE Natl. Cony. Rec., part 4, 142 - 164 (1959).Google Scholar
  9. 9.
    A. K. Jain, Fundamentals of Digital Image Processing (Prentice-Hall, Englewood Cliffs, New Jersey, 1989 ).Google Scholar
  10. 10.
    P.-S. Yeh, R. F. Rice and W. Miller, “On the optimality of code options for a universal noiseless coder,” JPL Publication 91 - 2 (1991).Google Scholar
  11. 11.
    H. B. Barlow, “Critical limiting factors in the design of the eye and visual cortex,” Proc. R. Soc. London B212, 1 - 34 (1981).CrossRefGoogle Scholar
  12. 12.
    T. N. Cornsweet, Visual Perception ( Academic Press, New York, 1970 ).Google Scholar
  13. 13.
    R. L. De Valois, H. Morgan and D. M. Snodderly, “Psychophysical studies of monkey vision-III,” Vision Res. 14, 75 - 81 (1974).CrossRefGoogle Scholar
  14. 14.
    R. L. Valois and K. K. Valois, Spatial Vision ( Oxford University Press, Oxford, 1990 ).Google Scholar
  15. 15.
    R. P. Dooley, “Predicting brightness appearance at edges using linear and non-linear visual describing functions,” Proc. of the SPSE Annual Meeting, Denver, Colorado (14 May, 1975 ).Google Scholar
  16. 16.
    P.G. Roetling, “Visual performance and image coding,” Proc. of the SPIE 74, 195-199, Pacific Grove, California (24-26 February 1976 ).Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Friedrich O. Huck
    • 1
  • Carl L. Fales
    • 1
  • Zia-ur Rahman
    • 2
  1. 1.Research and Technology GroupNASA Langley Research CenterUSA
  2. 2.Department of Computer ScienceCollege of William & MaryUSA

Personalised recommendations