Roy S. Berns

Methods for characterizing CRT displays

Abstract Computer-controlled CRT displays can be described by a two-stage model. The first stage consists of a linear transformation matrix relating radiometric scalars of each channel with either spectral radiance or tristimulus values. The second stage is non-linear and relates digital counts with the radiometric scalars for each channel. The term system gamm, Γ, is introduced to define the non-linear stage. Γ can be characterized by either direct measurement or using a theoretical model with gain, k g , offset, k o , and exponential, γ, parameters. Techniques and recommendations are given both to determine the transformation matrix coefficients and estimate Γ using several methods. Special attention is given to Macintosh imaging systems. Key issues include channel and spatial independence tests, including optical flare due to internal reflections, and problems arising from preset video look-up table entries.

A critical review of spectral models applied to binary color printing

A critical review of binary color printing models is presented. The goal is to provide an understanding of the application of color printer models as a component for device profiles within a color management system. A short description of a modern color management system is pre- sented, followed by a brief explanation of the halftoning process. This leads into the discussion of the individual models, which takes an historical approach. The discussion starts with early models proposed in the 1930s by Murray, followed by Neugebauer, Yule and Nielsen, and other much more recent model forms. To aid in gathering the appro- priate data for printer modeling, experimental techniques are then discussed, followed by an explanation of the model optimization methods needed for parameter fitting. The re- view concludes with procedures for model evaluation and a presentation of the results from an application of the models to a sample dataset for an electrophotographic printer.

Precision requirements for digital color reproduction

An environment was established to perform device-independent color reproduction of full-color pictorial images. In order to determine the required precision for this environment, an experiment was performed to psychophysically measure colorimetric tolerances for six images using paired comparison techniques. These images were manipulated using 10 linear and nonlinear functions in the CIELAB dimensions of lightness, chroma, and hue angle. Perceptibility tolerances were determined using probit analysis. From these results, the necessary precision in number of bits per color channel was determined for both the CIELAB and the CRT rgb device color spaces. For both the CIELAB color space and the CRT rgb device space, approximately eight color bits per channel were required for imperceptible color differences for pictorial images, and 10 bits per channel were required for computational precision.

Suprathreshold color-difference ellipsoids for surface colors

The RIT-DuPont visual color-difference data [Color Res. Appl. 16, 297–316 (1991)] have been used to estimate contours of equal color-differences (ellipsoids) at 19 color centers, in CIELAB and x, y, Y/100 color spaces. The ellipsoid fits are better in the CIELAB space than in x, y, Y/100, since the design of the RIT-DuPont experiment emphasized directional balance in CIELAB. The ellipsoids estimated are hardly tilted with respect to L* or Y/100, and they appear to be in overall good agreement with those reported for object colors in recent publications. From the characteristics and accuracy of the RIT-DuPont experiment, the current ellipsoids can be considered highly reliable and representative of color discrimination under the observational conditions employed, these closely following the “reference conditions” recently suggested by the CIE for industrial color-difference evaluation [Color Res. Appl. 20, 399–403 (1995)].

Colorimetric characterization of a desktop drum scanner using a spectral model

A desktop drum scanner was colorimetrically characterized to an average CIELAB error of less than unity for Kodak Ektachrome transparencies and Ektacolor paper, and Fuji Photo Film Fujichrome transparencies and Fujicolor paper. Independent verification on spectrally similar materials yielded an average ΔE* ab error of less than 2.1. The image formation of each medium was first modeled using either Beer-Bouguer or Kubelka-Munk theories and eigenvector analysis. Scanner digital values were then empirically related to dye concentrations using polynomial step-wise multiple-linear regression. These empirical matrices were required because the scanners system spectral responsivities had excessively wide bandwidths. From these estimated dye concentrations, either a spectral transmittance or spectral reflectance factor was calculated from an a priori spectral analysis of each medium. The spectral estimates can be used to calculate tristimulus values for any illuminant and obsetver of interest. The methods used in this research are based on historical methods commonly used in photographic science.

Performance of recent advanced color-difference formulas using the standardized residual sum of squares index.

The standardized residual sum of squares (STRESS) index was used to reevaluate four experimental datasets employed during the development of CIEDE2000, the current CIE recommended color-difference formula. This index enables statistical inferences not achievable by other metrics used commonly for performance evaluation. It was found that CIEDE2000 was statistically superior at a 95% confidence level to either CIE94, the previous recommended equation by the CIE, or the simple Euclidean distance in CIELAB, DeltaE*ab. Recent formulas based on the CIECAM02 color-appearance space and chroma-compressed variants of CIELAB were also evaluated and found to have only slightly reduced performance compared with CIEDE2000. These formulas have the advantage of simplicity and easier interpretation when used for quantifying color accuracy. Finally, each experimental dataset was evaluated separately rather than weight averaged as used during the development of CIEDE2000. Significant differences were found between datasets, suggesting that combining datasets may obscure important differences and that the practice of parameter optimization during formula development using combined data is likely suboptimal.

Multispectral-based color reproduction research at the Munsell Color Science Laboratory

The traditional techniques of image capture, scanning, proofing, and separating do not take advantage of colorimetry and spectrophotometry. For critical color-matching applications such as catalog sales, art-book reproductions, and computer-aided design, typical images, although pleasing, are unacceptable with respect to color accuracy. The limitations that lead to these errors have a well-defined theoretical basis and are a result of current hardware and software. This has led us to a re-examination of the traditional graphic reproduction paradigm. A research and development program has begun that will alleviate the theoretical limitations associated with traditional techniques. There are four main phases: (1) Multi-spectral image capture, (2) Spectral-based separation and printing algorithm development, (3) Implementation on press, and (4) Systems integration with data and image archives. This paper describes this new paradigm, summarizes recent research results, and considers implementation opportunities.

ERROR PROPAGATION ANALYSIS IN COLOR MEASUREMENT AND IMAGING

We apply multivariate error-propagation analysis to color-signal transformations. Results are given that indicate how linear, matrix, and nonlinear transformations influence the mean, variance, and covariance of color-measurements and color-images. Since many signal processing paths include these steps, the analysis is applicable to color-measurement and imaging systems. Expressions are given that allow image noise or error propagation for a spectrophotometer, colorimeter, or digital camera. In a computed example, error statistics are propagated from tristimulus values to CIELAB coordinates. The resulting signal covariance is interpreted in terms of CIELAB error ellipsoids and the mean value of color-difference measures, and . The application of this analysis to system design is also illustrated by relating a tolerance to equivalent tristimulus-value error statistics.

Relative significance of the terms in the CIEDE2000 and CIE94 color-difference formulas.

CIELAB-based color-difference formulas are used to improve the prediction of visually perceived color differences through the introduction of various corrections to CIELAB. In our study we analyze the relative importance of these corrections. From the combined dataset employed for the development of CIEDE2000, we found that the improvement of CIE94 over CIELAB was considerably greater than that of CIEDE2000 over CIE94. Chroma-difference correction was the most important correction in both CIE94 and CIEDE2000. With an arbitrary value of 100 assigned to this correction, the score of the hue-difference correction in CIE94 was 21, and the scores of the four remaining corrections in CIEDE2000 were as follows: hue difference, 29; rotation term, 8; lightness difference, 8; and gray correction, 6. At 95% confidence level each of the corrections introduced in CIEDE2000 or CIE94 was statistically significant for the whole combined dataset, in agreement with the results reported by CIE TC 1-47 and 1-29. For the combined dataset, the differences between CMC and CIEDE2000 were found to be statistically significant at 95% confidence level, but the differences between CMC and CIE94 were not. From subsets of the combined dataset it was concluded that further analyses of the lightness-difference and gray corrections proposed by CIEDE2000 would be desirable, using new experimental data.

Spectral modeling of a dye diffusion thermal transfer printer

A model was derived and tested that predicted the spectral reflectance factor from digital data for a dye diffusion thermal transfer printer. The model was based on the Kubelka-Munk turbid media theory and included terms to account for back diffusion onto the donor supply and dye transfer inhibition. The average colorimetric characterization accuracy of the printers color gamut based on 45 samples to estimate the model parameters was 3.0 ΔE* ab with a maximum of 7.4. The spectral model had similar performance to look-up table and multidimensional interpolation methods and superior performance to multiple-linear regression methods based on tristimulus data.