Abstract

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. Among other benefits, our proposed methodology allows one to determine the marginal posterior distribution of each random individual parameter of the color-difference model. In this manner, it is possible to analyze the effect of individual parameters on the statistical significance calculation of a color-difference equation.

Highlights

  • Most of the published work regarding color-difference models has been based on the CIE TC1.3 Guidelines for Coordinated Research on Color-Difference Evaluation [1]

  • We present a Bayesian approach for finding ellipsoidal coefficients of passfail methods

  • We applied the Bayesian approach to the threshold and constant stimuli method to fit the observed frequencies to those predicted by the model

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Summary

Introduction

Most of the published work regarding color-difference models has been based on the CIE TC1.3 Guidelines for Coordinated Research on Color-Difference Evaluation [1]. Guidelines for step one, which are related to object colors that consist mainly for the determination of perceptual ellipsoids around different color centers, can be summarized as follows: 1. Prepared samples are well distributed in the neighborhood of a selected color center. 2. Selection of the psychophysical data-collection technique. There are two main techniques: Pass-Fail, with two variants: Threshold and Constant Stimuli Method, and the Gray Scale. A selected team of observers is asked if pairs of samples, viewed under very controlled conditions, match or not (threshold method), or if the perceived color difference of the sample pairs look less or greater than a standard selected pair (constant stimuli method). The Constant Stimuli and Threshold Methods have been widely used by many authors [2,3,4]

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