CIE 1931 Research Articles

How the CIE 1931 color‐matching functions were derived from Wright‐Guild data

How the CIE 1931 color‐matching functions were derived from Wright‐Guild data

Perception Based Color Image Difference

A good image metric is often needed in digital image synthesis. It can be used to check the convergence behavior in progressive methods, to compare images rendered using various rendering methods etc. Since images are rendered to be observed by humans, an image metric should correspond to human perception as well. We propose here a new algorithm which operates in the original image space. There is no need for Fourier or wavelet transforms. Furthermore, the new metric is view distance dependent. The new method uses the contrast sensitivity function. The main idea is to place a number of various rectangles in images, and to compute the CIE LUV average color difference between corresponding rectangles. Errors are then weighted according to the rectangle size and the contrast sensitivity function.

Colourfulness judgments of natural scenes

The purpose of this study was to examine the relationship between colourfulness judgments of images of natural scenes and statistical parameters of the chroma distribution over the images in the CIE 1976 L∗u∗v∗ (CIELUV) colour space. A comparative analysis of within-scenes and between-scenes colourfulness assessments was performed. Images were created by varying chroma in the CIELUV colour space while lightness and hue-angle were kept constant. Experiment 1 shows the results of a multidimensional analysis of the differences-scaling in perceived colourfulness. Experiment 2 includes a unidimensional investigation of the direct-scaling of the magnitude of perceived colourfulness. Both experiments confirm that colourfulness judgments highly correlate with a linear combination of the mean of the distribution of chroma values and its standard deviation. That was also verified in Experiment 3 with “Mondrian”-like stimuli (spatially scrambled versions of the images of natural scenes). Colourfulness judgments of natural scenes, but not “Mondrian”-like scenes, brought out systematic differences between observers. In order to interpret and quantify these differences, a model of individual strategies in colourfulness judgments is developed and discussed.

Chroma variations and perceived quality of color images of natural scenes

Transformations of natural images in the perceptually uniform CIELUV color space have been investigated with respect to perceptual image quality. To this end, digitized color images of four natural scenes were described on the basis of their color point distributions in the CIELUV color space. A new set of images was created by varying the chroma value of each pixel while the lightness and hue angle were kept constant. The chroma was changed in two different ways: (1) through the addition or subtraction of the same amount of chroma to or from the chroma value of each pixel; (2) through multiplication of the chroma value of each pixel by a constant. In three experiments, subjects judged the perceptual quality, colorfulness, and naturalness of the images on a ten-point numerical category scale. The results indicate that colorfulness is the main perceptual attribute underlying image quality when chroma varies. Colorfulness itself was found to depend on both the average chroma and its variability. In general, the subjects preferred slightly more colorful images to the original ones. The perceptual quality of the images was found to be closely related to the naturalness of the images. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 96–110, 1997

Chroma variations and perceived quality of color images of natural scenes

Transformations of natural images in the perceptually uniform CIELUV color space have been investigated with respect to perceptual image quality. To this end, digitized color images of four natural scenes were described on the basis of their color point distributions in the CIELUV color space. A new set of images was created by varying the chroma value of each pixel while the lightness and hue angle were kept constant. The chroma was changed in two different ways: (1) through the addition or subtraction of the same amount of chroma to or from the chroma value of each pixel; (2) through multiplication of the chroma value of each pixel by a constant. In three experiments, subjects judged the perceptual quality, colorfulness, and naturalness of the images on a ten-point numerical category scale. The results indicate that colorfulness is the main perceptual attribute underlying image quality when chroma varies. Colorfulness itself was found to depend on both the average chroma and its variability. In general, the subjects preferred slightly more colorful images to the original ones. The perceptual quality of the images was found to be closely related to the naturalness of the images. © 1997 John Wiley & Sons, Inc. Col Res Appl, 22, 96–110, 1997

How the CIE 1931 color‐matching functions were derived from Wright‐Guild data

How the CIE 1931 color‐matching functions were derived from Wright‐Guild data

Memory Representation of Object Colours

Memory colours, ie colours recalled in association with familiar objects, impose a powerful constraint on colour appraisal of images of natural scenes. The purpose of this study is to specify the memory representation of one particular object colour. To this end, the colour of a banana was manipulated by varying hue-angle and saturation in the CIELUV colour space. Subjects' task was to rate the similarity in colour of the resulting banana samples displayed on the screen to the typical ripe banana stored in their mind. In order to examine the dependence of memory colour on texture information and context, three ways of presentation were used: original (banana among other fruit), isolated (the same banana against a homogenous gray background), and contour (silhouette of the banana with its average colour against the gray background). The relationships between the similarity judgments and chromaticity coordinates of the manipulated banana-represented points in the CIELUV colour space is described by a bivariate normal distribution with four parameters: two means and two variances of the Gaussians on the hue and saturation dimensions. For all three types of presentation, the variance of hue is significantly smaller than the variance of saturation; this suggests that memory description of hue is more precise than that of saturation. The data show systematic differences in the hue of memory colour between the original, isolated, and contour presentations of the banana. A model describing the hue shift in terms of illuminant and surface information content in the images is discussed.

Practical Formula for the Computation of CIE 1976 Hue Difference

Practical Formula for the Computation of CIE 1976 Hue Difference

Color space selection for JPEG image compression

The Joint Photographic Experts Group's image compression algorithm has been shown to provide a very efficient and powerful method of compressing images. However, there is little substantive information about which color space should be utilized when implementing the JPEG algorithm. Currently, the JPEG algorithm is set up for use with any three-component color space. The objective of this research is to determine whether or not the color space selected will significantly improve the image compression. The RGB, XYZ, YIQ, CIELAB, CIELUV, and CIELAB LCh color spaces were examined and compared. Both numerical measures and psycho-physical techniques were used to assess the results. The final resuLts indicate that the device space, RGB, is the worst color space to compress images. In comparison, the nonlinear transforms of the device space, CIELAB and CIELUV, are the best color spaces to compress images. The XYZ, YIQ, and CIELAB LCh color spaces resulted in intermediate levels of compression.

Colour image edge enhancement by two-channel process

The authors present a method for colour image edge enhancement using a two-channel process. High and low frequency components of a colour image are defined in the CIELUV colour space. Both luminance and saturation influences on edge enhancement are studied.

Evaluation of Uniform Color Spaces Developed after the Adoption of CIELAB and CIELUV

Since the adoption of the color spaces CIELAB and CIELUV by the CIE in 1976, several other uniform spaces have been developed. We studied most of these spaces and evaluated their uniformity for small as well as larger color differences. Therefore, several criteria have been defined based on color discrimination data and appearance systems. The main difference between color spaces based on discrimination data and spaces that model appearance systems is reflected in a different size of the chroma distance unit compared with the lightness unit. If spaces based on the same kind of data (discrimination data or appearance systems) are compared with each other, they are all almost equally uniform. BFD (l:c), for example, is said to be more uniform than CMC(l:c), but, based on confidence intervals of 65%, there is no significant difference between them. If the proposed color difference formula of the CIE is compared with these distance functions, it also performs equally well. The SVF space and OSA 90 space on the other hand should be better than OSA 74. However, as opposed to what was expected, OSA 74 is slightly better; but, also in this case, the difference between the spaces is insignificant.

Perceptual Quality of Color Images of Natural Scenes Transformed in CIELUV Color Space

Perceptual Quality of Color Images of Natural Scenes Transformed in CIELUV Color Space

Review of colorimetric methods for developing and evaluating uniform CRT display scales

A Y113,u',v' uniform color space is used to develop and evaluate a pseudocolor scale, the heated object spectrum, and an achromatic scale. The Y113,u',v' uniform color space is found to be more reliable, compared to the CIELUV and CIELAB uniform color spaces, when previously reported colorimetric data from self-luminous objects are modeled. The CIELUV and CIELAB uniform color spaces do not reliably predict the color thresholds from self-luminous objects due to the metric lightness of the uniform color scales and the method of combination for the orthogonal components. This implies that the Y113,u',v' uniform color space, rather than the CIELUV and CIELAB uniform color spaces, is more appropriate for developing uniform display scales for imaging with CRT displays. The heated object uniform display scale, compared to the achromatic uniform display scale, has a perceived display range that is 14% greater in the number of display scale values. Thus, the heated object uniform display has a greater contrast sensitivity range for the display/observer combination compared to the achromatic uniform display.

Visualization of VDU colours by means of the CIELUV colour space

The CIE 1976 ( L ∗ u ∗ v ∗ ) system, abbreviated CIELUV, has been widely used for specification of colours, for specification of colour differences, and for selection of colours presented on CRT screens. However, VDU colours have not earlier been visually presented as a virtual colour atlas with coloured patches occupying the appropriate positions in the CIELUV colour space. In this paper, CIELUV is illustrated by displaying the colours of 4 096 digital RGB combinations in chroma ( C ∗ uv ) — lightness ( L ∗ ) diagrams at five-degree increments in hue angle ( h uv) around the entire CIELUV hue circle. The 4 096 colours are quite nonuniformly distributed in the space. In particular, some yellows, blue-greens, and oranges are completely inaccessible by the VDU because of sparse sampling. Thus sampling, as well as gamut constraints, limit the colours accessible on a VDU.

Visualization of VDU colours by means of the CIELUV colour space

Visualization of VDU colours by means of the CIELUV colour space

A fallacy in the definition of ΔH*

AbstractWhen a color differs from the reference, it is desirable to ascribe the difference to differences in the perceptual attributes of hue, chroma, and/or lightness through psychometric correlates of these attributes. To this end, the CIE has recommended the quantity ΔH* as a psychometric correlate of hue as defined by ΔH* = [(ΔE*)2 ‐ (ΔL*)2 ‐ (ΔC*)2]1/2, where the correlates correspond to either the 1976 CIELAB or CIELUV color spaces. Since ΔH* is defined as a “leftover,” this definition is valid only to the extent that ΔE* comprises exclusively ΔL*, ΔC*, and ΔH* and that ΔL*, ΔC*, and ΔH* are mutually independent compositionally, both psychophysically and psychometrically. It will be shown that as now defined ΔH* lacks psychometric independence of chroma and always leads to incorrect hue difference determination. Such a deficiency causes problems, especially in the halftone color printing industry, since it can suggest an incorrect adjustment for the hue of the inks. A revised definition herein of ΔH* provides a psychometric hue difference independent of chroma, valid for large and small psychometric color differences regardless of chroma. However, for small chromas, the seldom used metric ΔC might be a better color difference metric than ΔH* because complex appearance effects make the perceptual discrimination of lightness, chroma, and hue components more difficult than for high chromas.

Transformation of NCS data into CIELUV colour space

The CIE ( L ∗, u ∗, v ∗ ) system, abbreviated CIELUV, and the Swedish Natural Colour System (NCS) have been compared. The data for the NCS was transformed to CIELUV; the transformation involved taking the CIE tristimulus values of the nominal NCS notations, i.e. the colorimetric aimpoints representing the NCS, converting these values to CIELUV and plotting them in the CIELUV space. All the data has been calculated using CIE standard illuminant C and the 1931 standard observer. Although the data shows that no simple linear relationship exists between the NCS and CIELUV systems, the systems may nevertheless be considered closely related. Of the existing colour order systems, i.e. NCS, Munsell etc., the NCS is closest to CIELUV. As NCS represents the perceptual and cognitive aspects of colour better than CIELUV, the NCS may be considered as highly appropriate for a descriptive specification of colours for VDUs.

The Effect of Chromatic Adaptation on Color Rendering

Present-day calculations of color-rendering index are based on color differences determined using the test light source and a standard illuminant. Chromatic adaptation is corrected by the von Kries transformation and the color differences are calculated in the CIE 1964 uniform color space. The present article discusses the possibility of introducing either the CIE 1976 CIELUV or CIELAB color space for calculating the color differences, and investigates how different forms of chromatic-adaptation corrections influence the color differences. It is concluded that a change from the present system to a CIELUV color-space calculation would not affect the color-rendering indices considerably; changing, however, to other color spaces or to a single reference illuminant with a better chromatic-adaptation formula (Bartleson-type chromatic-adaptation correction) would change the color-rendering order of some light sources. In the present article some critical samples and light sources are pointed out, where a comparison between the different types of calculations is possible.

CIE提案簡易けい光測色法の測色精度

The accuracy of CIE proposed one monochromator method was studied on the basis of the two monochromator method regarding the Colorimetry of fluorescent materials. In all the experiments, the fluorescent materials were always illuminated normally and viewed at 45° from the normal.The results studied are summarized as follows:(1) A theoretical account is given to estimate the accuracy of the CIE proposed method on the basis of the measurement by use of the two-monochromator method. The accuracy is discussed on the total, the reflected, and the fluorescent spectral radiance factor (SRF), respectively.(2) It is confirmed that the CIE proposed method is able to give the total SRF's of fluorescent materials under D65 within an average deviation of 1 % from those measured and estimated by the two-monochromator method. This average deviation of the total SRF's corresponds to the color difference less than 1 CIE LUV unit. In the overlapping region by excitation and luminescence, however, the deviation of the reflected SRF shows an error from 2 to 4 % in some fluorescent materials, and the error of Q (μ) function (fluorescence radiant efficiency) is also significant.(3) A simplified procedure is given for estimating Q (μ) function without using the spectral characteristic of the light receiver to be used. This simplification in the CIE proposed method is used provided that the colorimetric accuracy is allowed within the color difference of 1.5 CIE LUV unit.

Unit color-difference figures derived from the proposed CIE 1976 L*a*b* space: erratum

Unit color-difference figures derived from the proposed CIE 1976 L*a*b* space: erratum