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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Franco Gori
  • Vol. 28, Iss. 9 — Sep. 1, 2011
  • pp: 1841–1848

Performance measures of color-difference equations: correlation coefficient versus standardized residual sum of squares

Eric Kirchner and Niels Dekker  »View Author Affiliations


JOSA A, Vol. 28, Issue 9, pp. 1841-1848 (2011)
http://dx.doi.org/10.1364/JOSAA.28.001841


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Abstract

For evaluating the performance of color-difference equations, several goodness-of-fit measures were proposed in the past, such as Pearson’s correlation coefficient (r), the performance factor P F / 3 , and the recently proposed standardized residual sum of squares (STRESS) measure. The STRESS shares its main advantage, which is the possibility to statistically test performance differences, with the correlation coefficient. We show, by mathematical analysis supported by instructive numerical examples, that the STRESS has no meaningful interpretation in this regression analysis context. In addition, we present objections to the use of the STRESS for evaluating color- difference equations. Therefore, we recommend using the correlation coefficient in combination with a graphical and diagnostics analysis to ensure proper application as with any statistical technique.

© 2011 Optical Society of America

OCIS Codes
(330.1690) Vision, color, and visual optics : Color
(330.1730) Vision, color, and visual optics : Colorimetry

ToC Category:
Vision, Color, and Visual Optics

History
Original Manuscript: January 5, 2011
Revised Manuscript: May 20, 2011
Manuscript Accepted: July 10, 2011
Published: August 22, 2011

Virtual Issues
Vol. 6, Iss. 10 Virtual Journal for Biomedical Optics

Citation
Eric Kirchner and Niels Dekker, "Performance measures of color-difference equations: correlation coefficient versus standardized residual sum of squares," J. Opt. Soc. Am. A 28, 1841-1848 (2011)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-28-9-1841


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