Linear discriminants and image quality

H. H. Barrett, T. Gooley, K. Girodias, J. Rolland, T. White, J. Yao

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


The use of linear discriminant functions, and particularly a discriminant function derived from the work of Harold Hotelling1, as a means of assessing image quality is reviewed. The relevant theory of ideal or Bayesian observers is briefly reviewed, and the circumstances under which this observer reduces to a linear discriminant are discussed. The Hotelling observer is suggested as a linear discriminant in more general circumstances, where the ideal observer is nonlinear and usually very difficult to calculate. Methods of calculation of the Hotelling discriminant and the associated figure of merit, the Hotelling trace, are discussed. Psychophysical studies carried out at the University of Arizona to test the predictive value of the Hotelling observer are reviewed, and it is concluded that the Hotelling model is quite useful as a predictive tool unless there are high-pass noise correlations introduced by post-processing of the images. In that case, we suggest that the Hotelling observer be modified to include spatial-frequencyselective channels analogous to those in the visual system.

Original languageEnglish (US)
Pages (from-to)451-460
Number of pages10
JournalImage and Vision Computing
Issue number6
StatePublished - 1992


  • Hotelling trace
  • ideal observer
  • image quality
  • linear discriminant functions
  • medical imaging

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition


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