Strip-pair comparison method for building threshold color-difference model: theoretical model validation.

This paper presents a method for developing color-difference models near a threshold, based on the serial exploration method described by Torgerson [Theory and Methods of Scaling; Wiley & Sons (1958); Chap. 7], involving the construction of color-control strips of patches arranged in arrays of 2 × n, where n is the number of pairs in the strip. The patches in the lower row should be calorimetrically identical, while the color of the patches in the upper row should vary progressively in constant steps of CIELAB color difference along selected color space vector directions.

Parametric effects by using the strip-pair comparison method around red CIE color center.

The strip comparison method, based on the serial exploration method described by Torgerson [Theory and Methods of Scaling; Wiley & Sons (1958); Chap. 7], for the development of near-threshold color difference models was presented and validated with theoretical data by the authors in a previous work. In this study, we investigate parametric effects derived from the use of the strip comparison method on chromaticity-discrimination ellipses around the red CIE color center.

Parametric effects on the evaluation of threshold chromaticity differences using red printed samples.

Results from different authors showed deviations of radial orientation in the a-b plane (tilt) for the major axes of chromaticity-discrimination ellipses centered around the International Commission on Illumination (CIE) red color center [Color Res. Appl.3, 149 (1978)CREADU0361-2317], which are not considered by most of the current advanced color-difference formulas (e.

Bayesian approach to color-difference models based on threshold and constant-stimuli methods.

An alternative approach based on statistical Bayesian inference is presented to deal with the development of color-difference models and the precision of parameter estimation. The approach was applied to simulated data and real data, the latter published by selected authors involved with the development of color-difference formulae using traditional methods. Our results show very good agreement between the Bayesian and classical approaches.