As part of a research program to improve the relationship between visual and numerical color‐difference evaluation for industrial colorimetry, a color‐difference tolerance data set for fitting and testing of color‐difference metrics has been extended to include 156 individual color‐tolerance determinations. These tolerances were designed to sample 19 color centers over a surface color gamut with balanced sampling of lightness and chromaticness differences. The tolerance determination procedures emphasized accurate estimation of population visual color‐difference response and rigorous estimation of tolerance precision. Tolerance accuracy was confirmed by excellent agreement of these results and the majority of previous experiments on five color centers selected for CIE color‐difference evaluations. The average uncertainty of the tolerance determinations was ± 11% of the tolerance value at a 2 ó level (95% confidence interval). The completed data set is suitable for estimating the parameters of color‐difference metrics or testing the performance of such metrics. The color tolerances indicated the systematic lack of uniformity of the CIELAB space, in general agreement with previous experiments. A simple modification of the CIELAB color‐difference metric was shown to account for much of the systematic lack of uniformity.
Observer production of achromatic appearance has previously been used to measure the time course of chromatic adaptation for changes from daylight to incandescent illuminants at constant luminance, indicating an exponential decay of chromatic adaptation with a time constant of the order of 10 s. The work extends previous results in several ways. The psychophysical technique was significantly improved to provide more reliable estimates of color appearance as a function of adaptation duration, and the time course of chromatic adaptation was measured for six chromaticity changes. Three observers tracked achromatic appearance on a computer-controlled CRT display during transitions of 2-min duration between the various chromaticities. The results indicate that observer differences are statistically significant. However, differences in time course for different chromaticity changes are not statistically significant (within observer). Single or piecewise exponential decay functions cannot be fitted to the data. However, sum-of-two-exponentials functions provided accurate descriptions of the data. The results suggest two stages of adaptation: one extremely rapid (a few seconds) and the other somewhat slower (approximately 1 min). Chromatic adaptation at constant luminance was 90% complete after approximately 60 s.
This research extends the previous RIT‐DuPont research on suprathreshold color‐difference tolerances in which CIELAB was sampled in a balanced factorial design to quantify global lack of visual uniformity. The current experiments sampled hue, specifically. Three complete hue circles at two lightnesses (L* = 40 and 60) and two chroma levels ($C^*_{ab}$ = 20 and 40) plus three of the five CIE recommended colors (red, green, blue) were scaled, visually, for hue discrimination, resulting in 39 color centers. Forty‐five observers participated in a forced‐choice perceptibility experiment, where the total color difference of 393 sample pairs were compared with a near‐neutral anchor‐pair stimulus of 1.03 $\Delta E^*_{ab}.$ A supplemental experiment was performed by 30 additional observers in order to validate four of the 39 color centers. A total of 34,626 visual observations were made under the recently established CIE recommended reference conditions defined for the CIE94 color‐difference equation. The statistical method logit analysis with three‐dimensional normit function was used to determine the hue discrimination for each color center. A three‐dimensional analysis was required due to precision limitations of a digital printer used to produce the majority of colored samples. There was unwanted variance in lightness and chroma in addition to the required variance in hue. This statistical technique enabled estimates of only hue discrimination. The three‐dimensional analysis was validated in the supplemental experiment, where automotive coatings produced with a minimum of unwanted variance yielded the same visual tolerances when analyzed using one‐dimensional probit analysis. The results indicated that the hue discrimination suprathresholds of the pooled observers varied with CIELAB hue angle position. The suprathreshold also increased with the chroma position of a given color center, consistent with previous visual results. The results were compared with current color‐difference formulas: CMC, BFD, and CIE94. All three formulas had statistically equivalent performance when used to predict the visual data. Given the lack of a hue‐angle dependent function embedded in CIE94, it is clear from these results that neither CMC nor BFD adequately predict the visual data. Thus, these and other hue‐suprathreshold data can be used to develop a new color‐difference formula with superior performance to current equations. © 1998 John Wiley & Sons, Inc. Col Res Appl, 23, 302–313, 1998
Every physical quantity with an a priori range of numerical values constituting a continuum is subject to error in its measurement. It is important to report the highest amount by which any measured quantity might be in error. Optical radiation measurements are typically based on determination of the ratio of the instrumental reading of a calibrated standard to the instrumental reading of the test sample. There are random and systematic errors in both the instrumental readings and the calibration values. The uncertainty in a calculated value due to random error in its constituents can be determined using well known techniques of error propagation. Examples of error propagation through spectral reflectance factor measurements and colorimetric calculations are presented. The standard deviations of CIELAB coordinates for typical measurements can be as high as 0.258 due only to random errors in the calibration chain.
The accuracy of spectrophotometric measurements is limited by the standards that are used to calibrate the instrument. Therefore, the procedure used in transferring the spectral reflectance factor scale from one material to another for use in calibration must induce the minimum amount of error. the Munsell Color Science Laboratory has been transferring the spectral reflectance factor scale to calibration materials using a statistical method to correct for the most pervasive systematic errors in the measurement process. This method is based on a statistical procedure in which a set of systematic spectrophotometric errors are estimated based on the measurement of seven NIST primary standards and corrected in subsequent measurements. the optimization of the spectral reflectance factor scale to NIST standards minimizes the induced error. the average reflectance factor error consistently found between the corrected measurements of the NIST standards and their certificate values have been 0.0006 and the average δab has been on the order of 0.2.
Observer production of achromatic appearance has been used to measure the time course of chromatic adaptation for changes from daylight to incandescent illuminants at constant luminance.
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