Using suprathreshold color-difference ellipsoids to estimate any perceptual color-difference

[EN] Relating instrumentally measured to visually perceived colour-differences is one of the challenges of advanced colorimetry. Lately, the use of color difference formulas is becoming more important in the computer vision field as it is a key tool in advancing towards perceptual image processing and understanding. In the last decades, the study of contours of equal color-differences around certain color centers has been of special interest. In particular, the contour of threshold level difference that determines the just noticeable differences (JND) has been deeply studied and, as a result, a set of 19 different ellipsoids of suprathreshold color-difference is available in the literature. In this paper we study whether this set of ellipsoids could be used to compute any color difference in any region of the color space. To do so, we develop a fuzzy multi-ellipsoid model using the ellipsoids information along with two different metrics. We see that the performance of the two metrics vary significantly for very small, small, medium and large color differences. Therefore, we also study how to adapt two metric parameters to optimize performance. The obtained results outperform the currently CIE-recommended colordifference formula CIEDE2000.S. Morillas acknowledges the support of grants PRX16/00050 and PRX17/00384 (Ministerio de Educacion, Cultura y Deporte) and MTM2015-64373-13 (MINECO/FEDER, UE). The authors thank Dr. Manuel Melgosa, Dr. Luis Gomez-Robledo, Dr. Esther Sanabria-Codesal, Dr. Francisco Montserrat and Mr. Fu Jiang for providing useful materials, information and suggestions.Morillas, S.; Fairchild, MD. (2018). Using suprathreshold color-difference ellipsoids to estimate any perceptual color-difference. Journal of Visual Communication and Image Representation. 55:142-148. https://doi.org/10.1016/j.jvcir.2018.05.022S1421485

Color Difference Makes a Difference: Four Planet Candidates around τ Ceti

The removal of noise typically correlated in time and wavelength is one of the main challenges for using the radial-velocity (RV) method to detect Earth analogues. We analyze τ Ceti RV data and find robust evidence for wavelength-dependent noise. We find that this noise can be modeled by a combination of moving average models and the so-called "differential radial velocities." We apply this noise model to various RV data sets for τ Ceti, and find four periodic signals at 20.0, 49.3, 160, and 642 days, which we interpret as planets. We identify two new signals with orbital periods of 20.0 and 49.3 days while the other two previously suspected signals around 160 and 600 days are quantified to a higher precision. The 20.0 days candidate is independently detected in Keck data. All planets detected in this work have minimum masses less than 4M⊕ with the two long-period ones located around the inner and outer edges of the habitable zone, respectively. We find that the instrumental noise gives rise to a precision limit of the High Accuracy Radial Velocity Planet Searcher (HARPS) around 0.2 m s−1. We also find correlation between the HARPS data and the central moments of the spectral line profile at around 0.5 m s−1 level, although these central moments may contain both noise and signals. The signals detected in this work have semi-amplitudes as low as 0.3 m s−1, demonstrating the ability of the RV technique to detect relatively weak signals

Uniform color spaces based on CIECAM02 and IPT color difference equations

Color difference equations based on the CIECAM02 color appearance model and IPT color space have been developed to fit experimental data. There is no color space in which these color difference equations are Euclidean, e.g. describe distances along a straight line. In this thesis, Euclidean color spaces have been derived for the CIECAM02 and IPT color difference equations, respectively, so that the color difference can be calculated as a simple color distance. Firstly, the Euclidean line element was established, from which terms were derived for the new coordinates of lightness, chroma, and hue angle. Then the spaces were analyzed using performance factors and statistics to test how well they fit various data. The results show that the CIECAM02 Euclidean color space has performance factors similar to the optimized CIECAM02 color difference equation. To statistical significance, the CIECAM02 Euclidean color space had superior fit to the data when compared to the CIECAM02 color difference equation. Conversely, the IPT Euclidean color space performed poorer than the optimized IPT color difference equation. The main reason is that the line element for the lightness vector dimension could not be directly calculated so an approximation was used. To resolve this problem, a new IPT color difference equation should be designed such that line elements can be established directly

Painting new lines:Maximizing color difference in metro maps

Each metro line usually has its own color on the map. For obvious reasons, these colors should be maximally different. Suppose a new metro line is built. We now explain a strategy to choose the color or several colors for the new lines, making them as different as possible from both the old ones and each other. This is illustrated by using the Moscow metro map

Optimizing Color-Difference Formulas for 3D-Printed Objects

Based on previous visual assessments of 440 color pairs of 3D-printed samples, we tested the performance of eight color-difference formulas (CIELAB, CIEDE2000, CAM02-LCD, CAM02-SCD, CAM02-UCS, CAM16-LCD, CAM16-SCD, and CAM16-UCS) using the standardized residual sum of squares (STRESS) index. For the whole set of 440 color pairs, the introduction of kL (lightness parametric factor), b (exponent in total color difference), and kL + b produced an average STRESS decrease of 2.6%, 26.9%, and 29.6%, respectively. In most cases, the CIELAB formula was significantly worse statistically than the remaining seven formulas, for which no statistically significant differences were found. Therefore, based on visual results using 3D-object colors with the specific shape, size, gloss, and magnitude of color differences considered here, we concluded that the CIEDE2000, CAM02-, and CAM16-based formulas were equivalent and thus cannot recommend only one of them. Disregarding CIELAB, the average STRESS decreases in the kL + b-optimized formulas from changes in each one of the four analyzed parametric factors were not statistically significant and had the following values: 6.2 units changing from color pairs with less to more than 5.0 CIELAB units; 2.9 units changing the shape of the samples (lowest STRESS values for cylinders); 0.7 units changing from nearly-matte to high-gloss samples; and 0.5 units changing from 4 cm to 2 cm samples.Beijing Institute of Graphic Communication BIGC Ec202003 BIGC Ec202102 BIGC Ec202302Ministry of Science and Innovation of the National Government of Spain PID2019-107816GB-I00/SR

Measuring color differences in gonioapparent materials used in the automotive industry

This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.This research was supported by the Ministry of Economy and Competitiveness of Spain, research projects FIS2013-40661-P and DPI2011-30090-C02, with European Research Development Fund (ERDF), as well as by the National Science Foundation of China (grant number 61178053)